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d9e0d2ab5fab72fa0ce45bc0a16cd13b755439b0
subsection
41
42
Centroid Detection Methodologies
We initiate at the mean of the cluster samples because the spring-like pulling of each sample on the center is the same as the mean of the samples pulling on the center with a spring constant equal to the number of samples (proved below).   Proposition The combined spring-like pull of each sample, S_i, on a center, C, ...
{ "cite_spans": [] }
1804.11195
Revealing patterns in HIV viral load data and classifying patients via a novel machine learning cluster summarization method
[ "Samir Farooq", "Samuel J. Weisenthal", "Melissa Trayhan", "Robert J. White", "Kristen Bush", "Peter R. Mariuz", "Martin S. Zand" ]
[ "q-bio.QM", "cs.LG", "stat.ML" ]
2,018
en
Quantitative Biology
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b8739bd35e2108d6867d45aa3d5eb49c147e9e39
abstract
0
60
Abstract
Extending ASP with constraints (CASP) enhances its expressiveness and performance. This extension is not straightforward as the grounding phase, present in most ASP systems, removes variables and the links among them, and also causes a combinatorial explosion in the size of the program. Several methods to overcome this...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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27a798f2e4320fc2a3e63b3dc5b72c5ed2930bd7
subsection
1
60
Introduction
Answer Set Programming (ASP) has emerged as a successful paradigm for developing intelligent applications. It uses the stable model semantics  for programs with negation. ASP has attracted much attention due to its expressiveness, ability to incorporate non-monotonicity, represent knowledge, and model combinatorial pro...
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1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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6ccfea7ed96c79edef07ad5c1d5917087f8bf2a4
subsection
2
60
Introduction
Once the input program is translated, they benefit from the features and performance of the target ASP and CLP solvers. However, the translation may result in a large propositional representation or weak propagation strength. Extensions of ASP systems with constraint propagators , that generate and propagate new cons...
{ "cite_spans": [ { "arxiv_id": "", "doi": "10.48550/arxiv.1705.04569", "end": 456, "openalex_id": "https://openalex.org/W4301210146", "raw": "Banbara, M., Kaufmann, B., Ostrowski, M., and Schaub, T. 2017. Clingcon: The Next Generation. Theory and Practice of Logic Programming 17, 4,...
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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9ffc78b0d219bdcdc908c6b4b8829af8cf64af49
subsection
3
60
Background: ASP and s(ASP)
ASP , is a logic programming and modelling language. An ASP program \Pi is a finite set of rules. Each rule r \in \Pi is of the form:a \leftarrow b_1 \wedge \dots \wedge b_m \wedge not\ b_{m+1} \wedge \dots \wedge not\ b_n.where a and b_1, \dots , b_n are atoms and not corresponds to default negation. An atom is an exp...
{ "cite_spans": [ { "arxiv_id": "", "doi": "", "end": 53, "openalex_id": "https://openalex.org/W1672891595", "raw": "Gelfond, M. and Lifschitz, V. 1988. The Stable Model Semantics for Logic Programming. In International Conference on Logic Programming 1988. 1070–1080.", "source...
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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6f2f4dc9c12e33443dbfe0e09a2258646719e3bb
subsection
4
60
Background: ASP and s(ASP)
The top-down evaluation makes the grounding phase unnecessary. The execution of an s(ASP) program starts with a query, and each answer is the resulting mgu of a successful derivation, its justification, and a (partial) stable model. This partial stable model is a subset of the ASP stable model  including only the liter...
{ "cite_spans": [ { "arxiv_id": "", "doi": "", "end": 380, "openalex_id": "https://openalex.org/W1672891595", "raw": "Gelfond, M. and Lifschitz, V. 1988. The Stable Model Semantics for Logic Programming. In International Conference on Logic Programming 1988. 1070–1080.", "sourc...
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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428455f188248f2ba1c71fa649854916e418176f
subsection
5
60
Dual of a Logic Program
The dual of a predicate [style=MyInline]p/1 is another predicate that returns the [style=MyInline]X such that p(X) is not true. It is used to give a constructive answer to a goal [style=MyInline]not p(X). The dual of a logic program is another logic program containing the dual of each predicate in the program . To synt...
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1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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bd998700fea95d92e361216de74d3cedb9c64efb
subsection
6
60
Dual of a Logic Program
At the end of the chain, unification has to be negated to obtain disequality, e.g., x = y is transformed into x \ne y (Section REF ).Example 2 Given the program below:2 [style=MyProlog] p(0). p(X) :- q(X), not t(X,Y). q(1). t(1,2).the resulting dual program is:2 [style=MyProlog] not p(X) :- not p1(X), not p2(X). not p1...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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be0414244682cbfb5edf5aab8f4c43e55fedaeae
subsection
7
60
Constructive Disequality
Unlike Prolog's negation as failure, disequality in s(ASP), denoted by “\=” , represents the constructive negation of the unification and is used to construct answers from negative literals. Intuitively, [style=MyInline]Xā means that X can be any term not unifiable with a. In the implementation reported in (marple2017b...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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4c0f10717352bc5e60c93d4806253a7051881c9a
subsection
8
60
Body
In (marple2017b 2017b) the universal quantifier is evaluated by [style=MyInline]forall(V, Goal) which checks if [style=MyInline]Goal is true for all the possible values of [style=MyInline]V. When [style=MyInline]forall/2 succeeds, the evaluation continues with the quantified variable unbound. Multiple quantified variab...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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f81ddf299fc05ffd74e9a7eb3a3e065d97567a06
subsection
9
60
Body
Note that leaving [style=MyInline]X unbound after the success of [style=MyInline]forall(X, p(X)) is consistent with the interpretation that the answer set [style=MyInline]{p(X)} corresponds to \forall x.p(x).Finally, in order to break infinite loops, s(ASP) uses three techniques to deal with odd loops over negation, ev...
{ "cite_spans": [ { "arxiv_id": "", "doi": "10.1016/0304-3975(93)90222-f", "end": 926, "openalex_id": "https://openalex.org/W2022530540", "raw": "Revesz, P. Z. 1993. A Closed-Form Evaluation for Datalog Queries with Integer (Gap)-Order Constraints. Theoretical Computer Science 116, 1...
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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4d13101658519b7db2a72284c1eb20f8a239e1cb
subsection
10
60
Body
The call [style=MyInline]apply(NV,V,Store) takes the object [style=MyInline]Store and makes it part of the global store but substituting f̭or [style=MyInline]NV so that the execution of [style=MyInline]NGoal can further constrain [style=MyInline]NV while r̭emains untouched. Note, however, that in the first iteration, [...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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9287484ff05508b8cb8d371349b17854bf0c4ee6
subsection
11
60
Body
Note that if a conjunction C_{i} \wedge \lnot A_{i.j} is inconsistent, it means that \lnot A_{i.j} has already been (successfully) checked.Each of the resulting constraint stores will be re-evaluated by [style=MyInline]evalforall/3, where [style=MyInline]apply/3 will apply them to a new variable [style=MyInline]NV, in ...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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3a889ba8f664126466ba81d897dac2dceac7e10b
subsection
12
60
Non-Monotonic Checking Rules
Non-monotonic rules are used by s(ASP) to ensure that partial stable models are consistent with the global constraints of the program. Given a consistency rule of the form \forall \vec{x} ( p_i(\vec{x}) \leftarrow \exists \vec{y} \ B_i \wedge \lnot p_i(\vec{x}) ), and in order to avoid contradictory rules of the form p...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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6a409239a0d39cdf203e6ba9172d8bf71e39459a
subsection
13
60
s(CASP): Design and Implementation
S(CASP) (available together with the benchmarks used in this paper at https://gitlab.software.imdea.org/joaquin.arias/sCASP) extends s(ASP) by computing partial stable models of programs with constraints. This extension makes the following contributions: [Table: Speed comparison: s(CASP) vs. s(ASP) (time in ms).]The in...
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1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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f71eff7f0cb9944f014b176c35bca05b1f75ac44
subsection
14
60
s(CASP) Programs
An s(CASP) program is a finite set of rules of the form:a \leftarrow c_a \wedge b_1 \wedge \dots \wedge b_m \wedge not\ b_{m+1} \wedge \dots \wedge not\ b_n.where the difference w.r.t. an ASP program is c_a, a simple constraint or a conjunction of constraints. A query to an s(CASP) program is of the form \leftarrow \ c...
{ "cite_spans": [ { "arxiv_id": "", "doi": "10.1016/0743-1066(94)90033-7", "end": 489, "openalex_id": "https://openalex.org/W2063727779", "raw": "Jaffar, J. and Maher, M. 1994. Constraint Logic Programming: A Survey. Journal of Logic Programming 19/20, 503–581.", "source_ref_id...
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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f6c61637230513738fc9e37ef6646d24a5907009
subsection
15
60
The Interpreter and the Disequality Constraint Solver
The s(CASP) interpreter carries the environment (the call path and the model) implicitly and delegates to Prolog all operations that Prolog can do natively, such as handling the bindings due to unification, the unbinding due to backtracking, and the operations with constraints, among others. The clauses of the program,...
{ "cite_spans": [ { "arxiv_id": "", "doi": "10.1145/2967973.2968596", "end": 2668, "openalex_id": "https://openalex.org/W2507879277", "raw": "Arias, J. and Carro, M. 2016. Description and Evaluation of a Generic Design to Integrate CLP and Tabled Execution. In 18th Int'l. ACM SIGPLAN...
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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6b64737773e2bac396a24a7ba9c0479b0bc4cd18
subsection
16
60
Integration of Constraint Solvers in s(CASP)
Holzbaur's CLP({Q})  solver was integrated in the current implementation of s(CASP). Since the interpreter already deals with the CLP(\ne ) constraint solver, only two details have to be taken in consideration:The compiler is extended to support CLP({Q}) relations \lbrace <, >, =, \ge , \le , \ne \rbrace during the con...
{ "cite_spans": [ { "arxiv_id": "", "doi": "", "end": 84, "openalex_id": "", "raw": "Holzbaur, C. 1995. OFAI CLP(Q,R) Manual, Edition 1.3.3. Tech. Rep. TR-95-09, Austrian Research Institute for Artificial Intelligence, Vienna.", "source_ref_id": "227603c1791e52ac306ca422589df3d...
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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b7e5525acd1b87018741beb334858327c0924046
subsection
17
60
Extending
Extending s(ASP) to programs with constraints requires a generalization of forall (Algorithm REF ) which we will call C-forall (Algorithm REF ). A successful evaluation of [style=MyInline]Goal in s(CASP) returns, on backtracking, a (potentially infinite) sequence of models and answer constraint stores A_1, A_2, \dots ....
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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252fcff7c818f133a8605e3122959341ccad8037
subsection
18
60
Examples and Evaluation
The expressiveness of s(CASP) allows the programmer to write programs / queries that cannot be written in [C]ASP without resorting to a complex, unnatural encoding. Additionally, the answers given by s(CASP) are also more expressive than those given by ASP. This arises from several points:s(CASP) inherits from s(ASP) t...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.017669793218374252, 0.006462139543145895, -0.0366823710501194, 0.04068019986152649, -0.023254547268152237, -0.04101589322090149, -0.004741699900478125, 0.009025633335113525, 0.0177918653935194, 0.046570129692554474, -0.01260384265333414, 0.03402732312679291, 0.0025940111372619867, -0.00...
f38fcfdfc18d07440d68c69880f2af30b9680bc1
subsection
19
60
Stream Data Reasoning
Let us assume that we deal with data streams, some of whose items may be contradictory . Moreover, different data sources may have a different degree of trustworthiness which we use to prefer a given data item in case of inconsistency. Let us assume that [style=MyInline]p(X) and [style=MyInline]q(X) are contradictory a...
{ "cite_spans": [ { "arxiv_id": "", "doi": "10.4230/oasics.iclp.2016.17", "end": 88, "openalex_id": "https://openalex.org/W2574190931", "raw": "Arias, J. 2016. Tabled CLP for Reasoning over Stream Data. In Technical Communications of the 32nd Int'l Conference on Logic Programming (IC...
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.0265469029545784, -0.035762034356594086, -0.046197716146707535, 0.0189947672188282, 0.006518485490232706, -0.04207836836576462, 0.005950168240815401, 0.018140384927392006, 0.014272774569690228, 0.04387867450714111, 0.003589171916246414, -0.023556562140583992, -0.03866083547472954, -0.01...
bbf220c36f7a8bf51ba814cd4c2be22112f585d1
subsection
20
60
Stream Data Reasoning
For example, the rule [style=MyInline]incompt(p(X),q(X)) does not have to be grounded w.r.t. the stream database, and if timestamps were used as trustworthiness measure, for a query such as [style=MyInline]?-T.>.10,validstream(T,p(A)) the reasoner would validate streams received after [style=MyInline]T=10 regardless ho...
{ "cite_spans": [ { "arxiv_id": "", "doi": "10.4230/oasics.iclp.2016.17", "end": 439, "openalex_id": "https://openalex.org/W2574190931", "raw": "Arias, J. 2016. Tabled CLP for Reasoning over Stream Data. In Technical Communications of the 32nd Int'l Conference on Logic Programming (I...
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.023929346352815628, -0.026203244924545288, -0.04279202222824097, 0.021853841841220856, 0.0018399119144305587, -0.04846913740038872, 0.011422906070947647, 0.007042980752885342, -0.0017702833283692598, 0.038763102144002914, 0.012781140394508839, -0.013658651150763035, -0.026935776695609093,...
56a4ad7415b070e6159983f6e9d0f8b013fe4b33
subsection
21
60
Stream Data Reasoning
For the query [style=MyInline]?- validstream(Pr,Data), it returns: [style=MyInline]{Pr=1, Data=p(A), Aā, Ab̄} because [style=MyInline]q(a) and [style=MyInline]q(b) are more reliable than [style=MyInline]p(X); [style=MyInline]{Pr=2, Data=q(b)}; and [style=MyInline]{Pr=3, Data=p(a)}. The justification tree and the model ...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.014170977286994457, -0.027121633291244507, -0.03215545788407326, 0.0004392678674776107, -0.009922734461724758, -0.056805942207574844, -0.0004526151460595429, 0.01655060239136219, -0.024192864075303078, 0.040331609547138214, 0.014483684673905373, -0.01361420564353466, -0.02869279682636261,...
dfc968e694660348dc0617b64f66e86ee569af95
subsection
22
60
Yale Shooting Scenario
In the spoiling Yale shooting scenario , there is a gun and three possible actions: load, shoot, and wait. If we load the gun and shoot within 35 minutes, the turkey is killed. Otherwise, the gun powder is spoiled. The executable plan must ensure that we kill the turkey within 100 minutes, assuming that we are not allo...
{ "cite_spans": [ { "arxiv_id": "", "doi": "10.1017/s1471068417000242", "end": 106, "openalex_id": "https://openalex.org/W2963268497", "raw": "Janhunen, T., Kaminski, R., Ostrowski, M., Schellhorn, S., Wanko, P., and Schaub, T. 2017. Clingo goes Linear Constraints over Reals and Inte...
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.02099490538239479, -0.03164493665099144, -0.02865438349545002, 0.016402268782258034, -0.00575605221092701, 0.0024851346388459206, 0.003473085118457675, 0.027937261387705803, -0.006438844371587038, 0.06106221675872803, -0.0035150444600731134, 0.004897793754935265, -0.05907868593931198, 0...
f2d7f9cf84ffe4252c92c0d02f3614b369439957
subsection
23
60
Yale Shooting Scenario
The query [style=MyInline]?-T.<.100, holds(T,st(dead,,),Actions), sets an upper bound to the duration [style=MyInline]T of the plan, and returns in [style=MyInline]Actions the plan with the actions in reverse chronological order: [style=MyInline]{T=55, Actions=[shoot, load, load]}, [style=MyInline]{T=66, Actions=[shoot...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ 0.0018931848462671041, -0.013184577226638794, -0.0324120856821537, 0.018662892282009125, -0.020921360701322556, 0.0029585184529423714, -0.004722947720438242, 0.04648173972964287, -0.039126455783843994, 0.03299196437001228, -0.02136389911174774, 0.004581793211400509, -0.032595206052064896, ...
dab0de9980bfa35e8341996ae4ca5ea56d3b0006
subsection
24
60
The Traveling Salesman Problem (TSP)
Let us consider a variant of the traveling salesman problem (visiting every city in a country only once, starting and ending in the same city, and moving between cities using the existing connections) where we want to find out only the Hamiltonian cycles whose length is less than a given upper bound. Solutions for this...
{ "cite_spans": [ { "arxiv_id": "", "doi": "10.1007/11562931_8", "end": 422, "openalex_id": "https://openalex.org/W1572712485", "raw": "Dovier, A., Formisano, A., and Pontelli, E. 2005. A Comparison of CLP(FD) and ASP Solutions to NP-Complete Problems. In International Conference on ...
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.03637581318616867, -0.03637581318616867, -0.059080179780721664, 0.04968106001615524, 0.001654573017731309, -0.014258891344070435, -0.022139808163046837, -0.010223068296909332, -0.006267351098358631, 0.05807312950491905, -0.02395554818212986, 0.038267843425273895, -0.0035971468314528465, ...
18d6d1c2237e79e9671c396d85a4ef1b7a01ff7e
subsection
25
60
The Traveling Salesman Problem (TSP)
The ASP encoding is more compact, even if the CLP(\mathit {FD}) version uses the non-trivial library predicate [style=MyInline]circuit/1, which does the bulk of the work. We will show that s(CASP) is more expressive also in this problem.Finding the (bounded) path length in ASP requires using a specific, ad-hoc builtin ...
{ "cite_spans": [ { "arxiv_id": "", "doi": "", "end": 683, "openalex_id": "", "raw": "Hölldobler, S. and Schweizer, L. 2014. Answer Set Programming and clasp, a Tutorial. In Young Scientists’ International Workshop on Trends in Information Processing (YSIP). 77.", "source_ref_i...
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.02765805274248123, -0.027719072997570038, -0.057634927332401276, 0.06126571074128151, -0.006433967500925064, -0.03444670885801315, -0.03353138267993927, -0.017970869317650795, 0.009900758974254131, 0.046376436948776245, -0.010465208441019058, 0.021235525608062744, -0.0034496288280934095, ...
57f04f72f7479e0a9ddfb2a653cf7ed0d57e1c71
subsection
26
60
Towers of Hanoi
We will not explain this problem here as it is widely known. Let us just remind the reader that solving the puzzle with three towers (the standard setup) and n disks requires at least 2^n - 1 movements. [Figure: s(CASP) code for the Towers of Hanoi.]Known ASP encodings, for a standard solver, set a bound to the number ...
{ "cite_spans": [ { "arxiv_id": "", "doi": "", "end": 408, "openalex_id": "", "raw": "Gebser, M., Kaminski, R., Kaufmann, B., Ostrowski, M., Schaub, T., and Thiele, S. 2008. A User’s Guide to gringo, clasp, clingo, and iclingo.", "source_ref_id": "ba13e661b868d8a012f6aa0ad6db22...
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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44e5c0167a47e51d15ce0d490f542c6a1f30d545
subsection
27
60
Towers of Hanoi
For reference, .3 shows the partial stable model for [style=MyInline]?-hanoi(7,T). [Table: Run time (ms) comparison for the Towers of Hanoi with ndisks.]Table REF compares execution time (in milliseconds) needed to solve the Towers of Hanoi with [style=MyInline]n disks by s(CASP) and clingo 5.2.0 with the standard and ...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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581908c8d3ec8565fd70c3ddeee4d6dcd38df495
subsection
28
60
Conclusion and Future Work
We have reported on the design and implementation of s(CASP), a top-down system to evaluate constraint answer set programs, based on s(ASP). Its ability to express non-monotonic programs à la ASP is coupled with the possibility of expressing control in a way similar to traditional logic programming — and, in fact, a si...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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91f7258f33c7028bda973c5b44b24e29e6c1c350
subsection
29
60
s(CASP) interpreter
The next figure shows a sketch of the s(CASP) interpreter's code implemented in Ciao Prolog.2 [style=MyProlog, basewidth=.51em] ??(Query) :- solve(Query,[],Mid), solvegoal(nmrcheck,Mid,Just), printjustmodel(Just).solve([],In,['$success'|In]). solve([Goal|Gs],In,Out) :- solvegoal(Goal,In,Mid), solve(Gs,Mid,Out).solvegoa...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.0236093457788229, -0.02400614134967327, -0.04218243807554245, 0.01585656777024269, -0.012705094181001186, -0.003983218688517809, -0.02901187166571617, 0.0060969190672039986, -0.011072127148509026, 0.03241515904664993, -0.005299512296915054, -0.013101889751851559, -0.016787512227892876, ...
9e16b42d1ee1b3a9fa7520955f93287f879a74f3
subsection
30
60
Handling Loops
Top-down evaluations may enter loops. Several techniques, notably tabling, have been used to enhance the termination properties of LP systems. This is more relevant in s(ASP) because the presence of negation introduces new types of loops:Odd loop over negation: it occurs when a cycle in the call graph contains an odd n...
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1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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d5810f0a0cd6acaf2bd4d2f9c76434c011c5035c
subsection
31
60
Handling Loops
We work around this by checking that the call and its ancestor are equal (Section REF ). Example 10 The next program generates infinitely many answers to the query [style=MyInline]?-nat(X). 2 [style=MyProlog] nat(0). nat(X) :- nat(Y), X is Y+1. However, if it fails, when the recursive call [style=MyInline]nat(Y) u...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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12932e0115a6b8c3fa8f2f5f494e1123dd0767a1
subsection
32
60
Handling Loops
2 [style=MyProlog, basewidth=.52em] validstream(P,Data) :- stream(P,Data), not cancelled(P,Data). cancelled(P,Data) :- higherprio(P1,P), stream(P1,Data1), incompt(Data,Data1). higherprio(PHi,PLo) :- PHi.>.PLo. incompt(p(X),q(X)). incompt(q(X),p(X)). stream(1,p(X)). stream(2,q(a)). stream(2,q(b)). stream(3,p(a)). not in...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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ba1410f0722b8667fac2ca41ee5cad01bad40060
subsection
33
60
Handling Loops
The output to a query consists of: (i) a justification tree with the successful derivation (note that variables could be free, ground, or constrained); (ii) a model with the positive atoms defined by the program that support the successful derivation; and (iii) the bindings of variables in the query (in this example, t...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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90e8cdb3141649bc0f75c7792196f090f254e590
subsection
34
60
Handling Loops
Answer 1 (in 18.907 ms): validstream(1,p(A.[a,b])) :- stream(1,p(A.[a,b])), not cancelled(1,p(A.[a,b])) :- not ocancelled1(1,p(A.[a,b])) :- forall(B,forall(C,not ocancelled1(1,p(A.[a,b]),B,C))) :- forall(C,not ocancelled1(1,p(A.[a,b]),D.=<.1,C)) :- not ocancelled1(1,p(A.[a,b]),D.=<.1,C) :- not higherprio(D.=<.1,1) :- n...
{ "cite_spans": [ { "arxiv_id": "", "doi": "10.1017/s1471068417000242", "end": 7085, "openalex_id": "https://openalex.org/W2963268497", "raw": "Janhunen, T., Kaminski, R., Ostrowski, M., Schellhorn, S., Wanko, P., and Schaub, T. 2017. Clingo goes Linear Constraints over Reals and Int...
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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f0379b721d5c76e81c746400bab9016122a73f6d
subsection
35
60
Handling Loops
2 [style=MyASP] include "incmodelc.lp". program base. action(load). action(shoot). action(wait). duration(load,25). duration(shoot,5). duration(wait,36). unloaded(0). sum at(0) = 0. sum armed(0) = 0. program step(n). 1 do(X,n) : action(X) 1. sum at(n),-1*at(N') = D :- do(X,n), duration(X,D), N' = n - 1. loaded(n) :- lo...
{ "cite_spans": [ { "arxiv_id": "", "doi": "10.1007/11562931_8", "end": 1067, "openalex_id": "https://openalex.org/W1572712485", "raw": "Dovier, A., Formisano, A., and Pontelli, E. 2005. A Comparison of CLP(FD) and ASP Solutions to NP-Complete Problems. In International Conference on...
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.018173137679696083, -0.028747431933879852, -0.06329318135976791, 0.019821079447865486, -0.0026740909088402987, -0.036315757781267166, -0.025375254452228546, 0.011161754839122295, -0.020568756386637688, 0.019302282482385635, -0.02694690227508545, 0.010086014866828918, -0.003648741869255900...
c4d753e510db62a3883d01d53edde2a083e98879
subsection
36
60
Handling Loops
2 [style=MyProlog, basewidth=0.52em] hamiltonianpath(Path) :- graph(Nodes,Edges), length(Nodes,N), length(Path,N), domain(Path,1,N), makedomains(Path,1,Edges,N), circuit(Path), labeling([ff],Path). makedomains([],,,). makedomains([X|Y],Node,Edges,N) :- findall(Z, member([Node,Z],Edges),Succs), reducedomains(N,Succs,X),...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.008620279841125011, -0.03539654612541199, -0.022900955751538277, 0.00958910770714283, -0.029797179624438286, -0.0580076165497303, 0.021451527252793312, -0.017332101240754128, -0.0026432981248944998, 0.03524397686123848, -0.029293693602085114, 0.021893983706831932, -0.013372876681387424, ...
f8c78f3623cf9d315a1f006de4b7b8ecd76d1e22
subsection
37
60
Handling Loops
Answer 1 (in [2346.489] ms): [ travelpath(b,61/10,[b,[31/10],c,[1],a,[1],d,[1],b]), path(b,b,b,61/10,[], [b,[31/10],c,[1],a,[1],d,[1],b]), cycledist(d,b,1), cycle(d,b), edge(d,b), distance(d,b,1), node(d), node(b), node(a), edge(d,a), distance(d,a,1), other(d,a), node(b), cycle(d,b), node(c), distance(d,b,1), path(b,b,...
{ "cite_spans": [ { "arxiv_id": "", "doi": "", "end": 1488, "openalex_id": "", "raw": "Gebser, M., Kaminski, R., Kaufmann, B., Ostrowski, M., Schaub, T., and Thiele, S. 2008. A User’s Guide to gringo, clasp, clingo, and iclingo.", "source_ref_id": "ba13e661b868d8a012f6aa0ad6db2...
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.011079645715653896, 0.010171603411436081, -0.03769521415233612, 0.006230393424630165, -0.005410102661699057, -0.01671103574335575, -0.009957946836948395, -0.006234208587557077, -0.029423633590340614, 0.010766791179776192, -0.030201954767107964, 0.008622589521110058, 0.012369219213724136, ...
75f35b331ddfdcdccace766258f17cc754a25cca
subsection
38
60
Handling Loops
1 move(D,P,T) : disk(D) : peg(P) 1 :- moves(M), T = 1..M. move(D,T) :- move(D,,T). on(D,P,0) :- initon(D,P). on(D,P,T) :- move(D,P,T). on(D,P,T+1) :- on(D,P,T), not move(D,T+1), not moves(T). blocked(D-1,P,T+1) :- on(D,P,T), disk(D), not moves(T). blocked(D-1,P,T) :- blocked(D,P,T), disk(D). :- move(D,P,T), blocked(D-1...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ 0.01174781285226345, 0.007948844693601131, -0.02187839336693287, 0.023510882630944252, -0.010389948263764381, -0.04159030690789223, 0.006400269456207752, 0.02364819310605526, -0.028026923537254333, 0.003982050810009241, -0.0030456585809588432, -0.024288984015583992, -0.018079426139593124, ...
3a8edfad7a4de42251687debc2c7588b7fa6a547
subsection
39
60
Handling Loops
Answer 1 (in [420.343] ms): [ hanoi(7,127), move(a,b,1), move(a,c,2), move(b,c,3), move(a,b,4), move(c,a,5), move(c,b,6), move(a,b,7), move(a,c,8), move(b,c,9), move(b,a,10), move(c,a,11), move(b,c,12), move(a,b,13), move(a,c,14), move(b,c,15), move(a,b,16), move(c,a,17), move(c,b,18), move(a,b,19), move(c,a,20), move(...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.018950743600726128, 0.04696488380432129, -0.009612695313990116, -0.007629123516380787, -0.0119395786896348, 0.030150296166539192, -0.041319333016872406, 0.017913181334733963, -0.02996719628572464, 0.012633828446269035, -0.016631489619612694, -0.009238868951797485, 0.008277598768472672, ...
76de50eaf7659285c3d1ed83cd7e76651b839a6f
subsection
40
60
Handling Loops
Several techniques, notably tabling, have been used to enhance the termination properties of LP systems. This is more relevant in s(ASP) because the presence of negation introduces new types of loops:Odd loop over negation: it occurs when a cycle in the call graph contains an odd number of intervening negations. These ...
{ "cite_spans": [ { "arxiv_id": "", "doi": "10.1007/978-3-540-74610-2_4", "end": 1611, "openalex_id": "https://openalex.org/W1963107927", "raw": "Gupta, G., Bansal, A., Min, R., Simon, L., and Mallya, A. 2007. Coinductive Logic Programming and its Applications. Logic Programming, 27–...
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.0394546240568161, 0.008856693282723427, -0.034541867673397064, 0.04427583888173103, -0.020383363589644432, -0.051873829215765, 0.031246352940797806, -0.005290367640554905, -0.015409578569233418, 0.06185191124677658, -0.02467058226466179, -0.02616577036678791, -0.029720652848482132, 0.02...
026266fb51dfacb852c579cea3cba36cec1f1619
subsection
41
60
Handling Loops
We work around this by checking that the call and its ancestor are equal (Section REF ). Example 10 The next program generates infinitely many answers to the query [style=MyInline]?-nat(X). 2 [style=MyProlog] nat(0). nat(X) :- nat(Y), X is Y+1. However, if it fails, when the recursive call [style=MyInline]nat(Y) u...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.034902095794677734, -0.0008976267999969423, -0.010540798306465149, 0.03914282098412514, -0.013446764089167118, -0.042590320110321045, -0.0014177069533616304, 0.0035619051195681095, -0.02861727774143219, 0.041736070066690445, -0.007192455232143402, -0.020288368687033653, -0.039356384426355...
6c99060b1cc478b8817a4d4c471426f5ee9c59de
subsection
42
60
Handling Loops
2 [style=MyProlog, basewidth=.52em] validstream(P,Data) :- stream(P,Data), not cancelled(P,Data). cancelled(P,Data) :- higherprio(P1,P), stream(P1,Data1), incompt(Data,Data1). higherprio(PHi,PLo) :- PHi.>.PLo. incompt(p(X),q(X)). incompt(q(X),p(X)). stream(1,p(X)). stream(2,q(a)). stream(2,q(b)). stream(3,p(a)). not in...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.022887013852596283, -0.03368968516588211, -0.02035418339073658, -0.0018958075670525432, -0.009818528778851032, -0.04876459762454033, 0.01890467293560505, 0.007777770049870014, -0.0332319438457489, 0.027205029502511024, 0.01846219040453434, -0.0426613911986351, -0.03729057312011719, 0.00...
5724822924466ffaacf61a64ac1332f3e252a967
subsection
43
60
Handling Loops
The output to a query consists of: (i) a justification tree with the successful derivation (note that variables could be free, ground, or constrained); (ii) a model with the positive atoms defined by the program that support the successful derivation; and (iii) the bindings of variables in the query (in this example, t...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.020993974059820175, -0.036068134009838104, -0.044062934815883636, 0.01489107497036457, -0.013769666664302349, -0.05089817941188812, -0.023801308125257492, 0.03573247790336609, -0.000691344088409096, 0.02612040936946869, -0.03734974563121796, -0.0004548567230813205, -0.00018964282935485244...
9f2146ace546a232ee8e2f12efa598c89d62e740
subsection
44
60
Handling Loops
Answer 1 (in 18.907 ms): validstream(1,p(A.[a,b])) :- stream(1,p(A.[a,b])), not cancelled(1,p(A.[a,b])) :- not ocancelled1(1,p(A.[a,b])) :- forall(B,forall(C,not ocancelled1(1,p(A.[a,b]),B,C))) :- forall(C,not ocancelled1(1,p(A.[a,b]),D.=<.1,C)) :- not ocancelled1(1,p(A.[a,b]),D.=<.1,C) :- not higherprio(D.=<.1,1) :- n...
{ "cite_spans": [ { "arxiv_id": "", "doi": "10.1017/s1471068417000242", "end": 7085, "openalex_id": "https://openalex.org/W2963268497", "raw": "Janhunen, T., Kaminski, R., Ostrowski, M., Schellhorn, S., Wanko, P., and Schaub, T. 2017. Clingo goes Linear Constraints over Reals and Int...
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.03737388551235199, -0.015552111901342869, -0.030890658497810364, -0.022439584136009216, 0.026558339595794678, 0.0006178132025524974, 0.01880897954106331, 0.031363554298877716, -0.01774115301668644, 0.02872449904680252, 0.007894279435276985, -0.04228588193655014, -0.050340332090854645, 0...
93306cbe9ed644706a1e030a816607b24b6cd719
subsection
45
60
Handling Loops
2 [style=MyASP] include "incmodelc.lp". program base. action(load). action(shoot). action(wait). duration(load,25). duration(shoot,5). duration(wait,36). unloaded(0). sum at(0) = 0. sum armed(0) = 0. program step(n). 1 do(X,n) : action(X) 1. sum at(n),-1*at(N') = D :- do(X,n), duration(X,D), N' = n - 1. loaded(n) :- lo...
{ "cite_spans": [ { "arxiv_id": "", "doi": "10.1007/11562931_8", "end": 1067, "openalex_id": "https://openalex.org/W1572712485", "raw": "Dovier, A., Formisano, A., and Pontelli, E. 2005. A Comparison of CLP(FD) and ASP Solutions to NP-Complete Problems. In International Conference on...
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.018173137679696083, -0.028747431933879852, -0.06329318135976791, 0.019821079447865486, -0.0026740909088402987, -0.036315757781267166, -0.025375254452228546, 0.011161754839122295, -0.020568756386637688, 0.019302282482385635, -0.02694690227508545, 0.010086014866828918, -0.003648741869255900...
1a362459522b676123b5b51a34ad5be970a5b9cc
subsection
46
60
Handling Loops
2 [style=MyProlog, basewidth=0.52em] hamiltonianpath(Path) :- graph(Nodes,Edges), length(Nodes,N), length(Path,N), domain(Path,1,N), makedomains(Path,1,Edges,N), circuit(Path), labeling([ff],Path). makedomains([],,,). makedomains([X|Y],Node,Edges,N) :- findall(Z, member([Node,Z],Edges),Succs), reducedomains(N,Succs,X),...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.008620279841125011, -0.03539654612541199, -0.022900955751538277, 0.00958910770714283, -0.029797179624438286, -0.0580076165497303, 0.021451527252793312, -0.017332101240754128, -0.0026432981248944998, 0.03524397686123848, -0.029293693602085114, 0.021893983706831932, -0.013372876681387424, ...
456ccb5401c9252af5e1cbfec7bc5ee78950c678
subsection
47
60
Handling Loops
Answer 1 (in [2346.489] ms): [ travelpath(b,61/10,[b,[31/10],c,[1],a,[1],d,[1],b]), path(b,b,b,61/10,[], [b,[31/10],c,[1],a,[1],d,[1],b]), cycledist(d,b,1), cycle(d,b), edge(d,b), distance(d,b,1), node(d), node(b), node(a), edge(d,a), distance(d,a,1), other(d,a), node(b), cycle(d,b), node(c), distance(d,b,1), path(b,b,...
{ "cite_spans": [ { "arxiv_id": "", "doi": "", "end": 1488, "openalex_id": "", "raw": "Gebser, M., Kaminski, R., Kaufmann, B., Ostrowski, M., Schaub, T., and Thiele, S. 2008. A User’s Guide to gringo, clasp, clingo, and iclingo.", "source_ref_id": "ba13e661b868d8a012f6aa0ad6db2...
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.011079645715653896, 0.010171603411436081, -0.03769521415233612, 0.006230393424630165, -0.005410102661699057, -0.01671103574335575, -0.009957946836948395, -0.006234208587557077, -0.029423633590340614, 0.010766791179776192, -0.030201954767107964, 0.008622589521110058, 0.012369219213724136, ...
2d57db5d0800f64d9462e9a9cd94322be324a22d
subsection
48
60
Handling Loops
1 move(D,P,T) : disk(D) : peg(P) 1 :- moves(M), T = 1..M. move(D,T) :- move(D,,T). on(D,P,0) :- initon(D,P). on(D,P,T) :- move(D,P,T). on(D,P,T+1) :- on(D,P,T), not move(D,T+1), not moves(T). blocked(D-1,P,T+1) :- on(D,P,T), disk(D), not moves(T). blocked(D-1,P,T) :- blocked(D,P,T), disk(D). :- move(D,P,T), blocked(D-1...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ 0.01174781285226345, 0.007948844693601131, -0.02187839336693287, 0.023510882630944252, -0.010389948263764381, -0.04159030690789223, 0.006400269456207752, 0.02364819310605526, -0.028026923537254333, 0.003982050810009241, -0.0030456585809588432, -0.024288984015583992, -0.018079426139593124, ...
2e726355688ce553b1c2d0b884567572f1535022
subsection
49
60
Handling Loops
Answer 1 (in [420.343] ms): [ hanoi(7,127), move(a,b,1), move(a,c,2), move(b,c,3), move(a,b,4), move(c,a,5), move(c,b,6), move(a,b,7), move(a,c,8), move(b,c,9), move(b,a,10), move(c,a,11), move(b,c,12), move(a,b,13), move(a,c,14), move(b,c,15), move(a,b,16), move(c,a,17), move(c,b,18), move(a,b,19), move(c,a,20), move(...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.022403573617339134, 0.0517357736825943, -0.0020278438460081816, -0.00939332414418459, -0.00015893203089945018, 0.02821812406182289, -0.04953814670443535, 0.015123938210308552, -0.020770614966750145, 0.014254044741392136, -0.017855709418654442, -0.011468859389424324, 0.001941999071277678, ...
40e59e4a5ceb953866180ab5692d82df60b60e94
subsection
50
60
s(CASP) encoding of stream.pl
The next figure shows the code of stream.pl with the dual program and the NMR generated by the extended compiler of s(CASP).2 [style=MyProlog, basewidth=.52em] validstream(P,Data) :- stream(P,Data), not cancelled(P,Data).cancelled(P,Data) :- higherprio(P1,P), stream(P1,Data1), incompt(Data,Data1).higherprio(PHi,PLo) :-...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.024329762905836105, -0.03583832085132599, -0.009738010354340076, -0.008516944013535976, -0.02159762568771839, -0.043500516563653946, 0.023185012862086296, -0.0018907461781054735, -0.018178638070821762, 0.05500907450914383, 0.014553594402968884, -0.03403724730014801, -0.04823215305805206, ...
2b23163971f4dfe19db68d140637807675195e82
subsection
51
60
s(CASP) output of stream.pl
The next figure shows the output for the query [style=MyInline]?-validstream(Pr,Data) when it is made to the program stream.pl (see .1). The output to a query consists of: (i) a justification tree with the successful derivation (note that variables could be free, ground, or constrained); (ii) a model with the positive ...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.03647197037935257, -0.009423197247087955, -0.041202645748853683, -0.00233100145123899, -0.022234167903661728, -0.0662294402718544, -0.012536286376416683, 0.01123153604567051, 0.0013247794704511762, 0.02855190634727478, -0.012345532886683941, 0.001216050237417221, -0.010285400785505772, ...
a601db2e33da99cef05a18147c176e4baa5a049c
subsection
52
60
s(CASP) output of stream.pl
The constraint store active at each call is shown close to each variable.[style=tree] ?- validstream(Pr, Data).Answer 1 (in 18.907 ms):validstream(1,p(A.[a,b])) :- stream(1,p(A.[a,b])), not cancelled(1,p(A.[a,b])) :- not ocancelled1(1,p(A.[a,b])) :- forall(B,forall(C,not ocancelled1(1,p(A.[a,b]),B,C))) :- forall(C,not ...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.020155493170022964, -0.0267620999366045, -0.03393324464559555, -0.014471979811787605, 0.013915072195231915, -0.005752173252403736, 0.0017002859385684133, 0.030454477295279503, -0.017760025337338448, 0.038785211741924286, 0.01335816364735365, -0.020140236243605614, -0.023283332586288452, ...
12e48f34c8d474ee491b0fe192f5cb856c9cfc8b
subsection
53
60
ASP + constraint encoding of yale_shooting_asp.pl
Nest figure shows the spoiled Yale shooting scenario model written in clingo + constraints using multi-shot solving .2 [style=MyASP] include "incmodelc.lp". program base. action(load). action(shoot). action(wait). duration(load,25). duration(shoot,5). duration(wait,36). unloaded(0). sum at(0) = 0. sum armed(0) = 0.prog...
{ "cite_spans": [ { "arxiv_id": "", "doi": "10.1017/s1471068417000242", "end": 117, "openalex_id": "https://openalex.org/W2963268497", "raw": "Janhunen, T., Kaminski, R., Ostrowski, M., Schellhorn, S., Wanko, P., and Schaub, T. 2017. Clingo goes Linear Constraints over Reals and Inte...
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.02988867647945881, -0.025860799476504326, -0.04314710199832916, -0.0027176723815500736, -0.007460725959390402, -0.013090599328279495, -0.004805989097803831, 0.0483345203101635, -0.029385190457105637, 0.012892256490886211, -0.0070678554475307465, -0.009505178779363632, -0.05083668604493141...
bb752edf4aee33c28e26907ff1a1ce0f3086cf3f
subsection
54
60
ASP encoding of hamicycle_asp.pl
The next figure shows an ASP program for the Travelling Salesman Problem described in section REF . The encoding for the Hamiltonian cycle part is from  and the code of #sum is adapted to run using clingo. The bound on the total distance is one of the global constraints in the program.[style=MyASP] 1 cycle(X,Y) : edge(...
{ "cite_spans": [ { "arxiv_id": "", "doi": "10.1007/11562931_8", "end": 206, "openalex_id": "https://openalex.org/W1572712485", "raw": "Dovier, A., Formisano, A., and Pontelli, E. 2005. A Comparison of CLP(FD) and ASP Solutions to NP-Complete Problems. In International Conference on ...
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.017197659239172935, -0.02618560940027237, -0.038454391062259674, 0.012390859425067902, 0.0002582223969511688, -0.05267641320824623, -0.01407705433666706, 0.008728536777198315, 0.006466289050877094, 0.03268623352050781, -0.027620019391179085, 0.042513467371463776, 0.010147687047719955, 0...
f94f82fea01ccb775bdd75a98e024dce08b6d445
subsection
55
60
CLP(FD) encoding of hamicycle_clpfd.pl
The next figure shows the program in CLP(\mathit {FD}) for the Hamiltonian cycle problem presented in , using SICStus Prolog 3.11.2. Note that the library predicate [style=MyInline]circuit/1 does the bulk of the work. Its implementation is non-trivial and shares a lot of code with the implementation of all_different, a...
{ "cite_spans": [ { "arxiv_id": "", "doi": "10.1007/11562931_8", "end": 132, "openalex_id": "https://openalex.org/W1572712485", "raw": "Dovier, A., Formisano, A., and Pontelli, E. 2005. A Comparison of CLP(FD) and ASP Solutions to NP-Complete Problems. In International Conference on ...
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
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8dd2bb07c7331806177dba0736422cfd75581f34
subsection
56
60
s(CASP) output of hamicycle_scasp.pl
The next figure shows the output to the query [style=MyInline]?-D.<.10,cycle(a,D,Cycle) to the program hamicycle_scasp.pl (Figure REF in Section REF ).[style=tree] ?- D.<.10, travelpath(b, D, Cycle).Answer 1 (in [2346.489] ms):[ travelpath(b,61/10,[b,[31/10],c,[1],a,[1],d,[1],b]), path(b,b,b,61/10,[], [b,[31/10],c,[1],...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.01896383799612522, -0.014577591791749, -0.055777788162231445, -0.028361845761537552, -0.037805624306201935, -0.00858941301703453, -0.010015896521508694, -0.018384089693427086, -0.011869561858475208, -0.002490624785423279, -0.030818143859505653, 0.012525591999292374, 0.008841145783662796, ...
d126ec478c7c9f434565c9cc6f91b232014c7962
subsection
57
60
ASP encoding of toh_asp.pl
The next program is part of :[style=MyASP, basewidth=0.48em] peg(a;b;c). disk(1..7). initon(1..7,a). goalon(1..7,b). moves(127). 1 move(D,P,T) : disk(D) : peg(P) 1 :- moves(M), T = 1..M. move(D,T) :- move(D,,T). on(D,P,0) :- initon(D,P). on(D,P,T) :- move(D,P,T). on(D,P,T+1) :- on(D,P,T), not move(D,T+1), not moves(T)....
{ "cite_spans": [ { "arxiv_id": "", "doi": "", "end": 81, "openalex_id": "", "raw": "Gebser, M., Kaminski, R., Kaufmann, B., Ostrowski, M., Schaub, T., and Thiele, S. 2008. A User’s Guide to gringo, clasp, clingo, and iclingo.", "source_ref_id": "ba13e661b868d8a012f6aa0ad6db221...
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ 0.024509677663445473, 0.010057209059596062, -0.024341803044080734, 0.02452494017779827, -0.004719562828540802, -0.01564285159111023, 0.010690554045140743, 0.03406326472759247, -0.007981670089066029, -0.0049522980116307735, -0.013033166527748108, -0.000019195877030142583, -0.02048069052398204...
39d1ed5d8c4105c8a939bda4e27d97d36599d84c
subsection
58
60
ASP incremental encoding of toh_aspI.pl
The next program is part of the clingo distribution and is available at https://github.com/potassco/clingo/tree/master/examples/gringo/toh2 [style=MyASP, basewidth=0.48em] include <incmode>.program base. peg(a;b;c). disk(1..7). initon(1..7,a). goalon(1..7,b).on(D,P,0) :- initon(D,P).program step(t). 1 move(D,P,t): disk...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ 0.004756317939609289, -0.011358712799847126, -0.026165470480918884, 0.02380066178739071, -0.01585184969007969, -0.04787594452500343, 0.032039351761341095, 0.016752002760767937, -0.019360922276973724, -0.01029836293309927, 0.0031085798982530832, 0.0034022738691419363, -0.03234448656439781, ...
03a7d30d50cda475cca7851ec363acdc1665f658
subsection
59
60
s(CASP) output of hanoi.pl
[style=tree] ?- hanoi(7,T).Answer 1 (in [420.343] ms):[ hanoi(7,127), move(a,b,1), move(a,c,2), move(b,c,3), move(a,b,4), move(c,a,5), move(c,b,6), move(a,b,7), move(a,c,8), move(b,c,9), move(b,a,10), move(c,a,11), move(b,c,12), move(a,b,13), move(a,c,14), move(b,c,15), move(a,b,16), move(c,a,17), move(c,b,18), move(a,...
{ "cite_spans": [] }
1804.11162
Constraint Answer Set Programming without Grounding
[ "Joaquín Arias", "Manuel Carro", "Elmer Salazar", "Kyle Marple", "Gopal Gupta" ]
[ "cs.PL", "cs.LO" ]
2,018
en
Computer Science
[ -0.026337234303355217, 0.052704986184835434, -0.014953933656215668, -0.01820412464439869, -0.00738922692835331, 0.007721112575381994, -0.03881919011473656, 0.019791072234511375, -0.020752396434545517, 0.014541937038302422, -0.014572455547749996, -0.010124423541128635, 0.0022850525565445423, ...
c8023be5990a223250b9beb0e6e0f4902130062c
abstract
0
16
Abstract
With the recent success of embeddings in natural language processing, research has been conducted into applying similar methods to code analysis. Most works attempt to process the code directly or use a syntactic tree representation, treating it like sentences written in a natural language. However, none of the existin...
{ "cite_spans": [] }
1806.07336
Neural Code Comprehension: A Learnable Representation of Code Semantics
[ "Tal Ben-Nun", "Alice Shoshana Jakobovits", "Torsten Hoefler" ]
[ "cs.LG", "cs.NE", "cs.PL", "stat.ML" ]
2,018
en
Computer Science
[ -0.04965818300843239, 0.02414236217737198, -0.009629474952816963, 0.031314872205257416, 0.007183955051004887, -0.033146150410175323, 0.0021689210552722216, 0.0011512258788570762, 0.017839709296822548, 0.023409849032759666, -0.040257617831230164, -0.036503493785858154, -0.003090283367782831, ...
ce7097cdd75db5420c6f58fac78399514847c8f5
subsection
1
16
Introduction
The emergence of the “Big Data era” manifests in the form of a dramatic increase in accessible code. In the year 2017 alone, GitHub reports  approximately 1 billion git commits (code modification uploads) written in 337 different programming languages. Sifting through, categorizing, and understanding code thus becomes ...
{ "cite_spans": [] }
1806.07336
Neural Code Comprehension: A Learnable Representation of Code Semantics
[ "Tal Ben-Nun", "Alice Shoshana Jakobovits", "Torsten Hoefler" ]
[ "cs.LG", "cs.NE", "cs.PL", "stat.ML" ]
2,018
en
Computer Science
[ -0.04161868244409561, 0.003936077933758497, 0.004988749977201223, 0.029535839334130287, -0.006510547362267971, -0.03151913359761238, -0.003920821938663721, -0.026362568140029907, 0.006899578496813774, 0.018993863835930824, -0.02251802757382393, -0.020351657643914223, -0.0033162981271743774, ...
a26ba25afc67c6c6e5ee83cb9dab642bd68a536d
subsection
2
16
Introduction
In turn, the XFG structure is used to train an embedding space for individual statements, called inst2vec (from the word “instruction”), which is fed to RNNs for a variety of high-level tasks.Neural Code Comprehension is evaluated on multiple levels, using clustering and analogies for inst2vec, as well as three differe...
{ "cite_spans": [] }
1806.07336
Neural Code Comprehension: A Learnable Representation of Code Semantics
[ "Tal Ben-Nun", "Alice Shoshana Jakobovits", "Torsten Hoefler" ]
[ "cs.LG", "cs.NE", "cs.PL", "stat.ML" ]
2,018
en
Computer Science
[ -0.051023103296756744, 0.005595909897238016, -0.020873088389635086, -0.004367632791399956, -0.029554950073361397, -0.026823749765753746, 0.010329737327992916, -0.032042019069194794, 0.011748741380870342, -0.00008719768811715767, -0.01489953976124525, -0.019164180383086205, -0.000063774110458...
8482f2152565d6bc7f0c140c49053264ba5ce5fd
subsection
3
16
Related Work
Distributed representations of code were first suggested by Allamanis et al. , followed by several works leveraging embeddings to apply NLP techniques to programming languages , .
{ "cite_spans": [] }
1806.07336
Neural Code Comprehension: A Learnable Representation of Code Semantics
[ "Tal Ben-Nun", "Alice Shoshana Jakobovits", "Torsten Hoefler" ]
[ "cs.LG", "cs.NE", "cs.PL", "stat.ML" ]
2,018
en
Computer Science
[ -0.02740357629954815, 0.0025366616901010275, -0.001251165522262454, 0.03744341805577278, -0.06216156482696533, 0.012412477284669876, 0.07452064007520676, -0.022078493610024452, 0.012816817499697208, -0.01876748353242874, 0.001800457714125514, -0.007613800000399351, -0.021819105371832848, 0...
04d91bc61417893cab9c302305d85eadb0513479
subsection
4
16
Code Representation
Previous research focuses on embedding high-level programming languages such as Java , , C , or OpenCL  in the form of tokens or statements, as well as lower level representations such as object code . To the best of our knowledge, however, no attempt has been made to train embeddings for compiler IRs prior to this wor...
{ "cite_spans": [] }
1806.07336
Neural Code Comprehension: A Learnable Representation of Code Semantics
[ "Tal Ben-Nun", "Alice Shoshana Jakobovits", "Torsten Hoefler" ]
[ "cs.LG", "cs.NE", "cs.PL", "stat.ML" ]
2,018
en
Computer Science
[ -0.06065216287970543, -0.025673437863588333, -0.04042460769414902, 0.030493881553411484, -0.012333318591117859, -0.05119433254003525, -0.004511538427323103, 0.0011955767404288054, 0.014568112790584564, 0.009747669100761414, -0.018686845898628235, -0.03046337328851223, 0.014644385315477848, ...
b179cc3e2929b313009f1c7e7f3fd0790373f885
subsection
5
16
Automated Tasks on Code
Learned representations of code are commonly used for two types of tasks: uncovering program semantics or optimizing programs. For the former task, code embeddings have been used to perform function or variable naming , , clone detection , code completion , , summarization , and algorithm classification . As for progra...
{ "cite_spans": [] }
1806.07336
Neural Code Comprehension: A Learnable Representation of Code Semantics
[ "Tal Ben-Nun", "Alice Shoshana Jakobovits", "Torsten Hoefler" ]
[ "cs.LG", "cs.NE", "cs.PL", "stat.ML" ]
2,018
en
Computer Science
[ -0.03299650922417641, 0.006349004339426756, -0.030279865488409996, 0.018283911049365997, -0.023183021694421768, -0.028005823493003845, 0.03614048659801483, -0.005028838757425547, 0.020390070974826813, 0.022633589804172516, -0.04200110584497452, -0.03253864496946335, -0.02348826266825199, 0...
aea957182a5a34be0ad1968a70ddc888ff1f139a
subsection
6
16
Embedding Evaluation
Previous works that use code embeddings do not evaluate the quality of the trained space on its own merit, but rather through the performance of subsequent (downstream) tasks. One exception is Allamanis et al. , who present empirical evidence of vector similarities for similar method names. To the best of our knowledge...
{ "cite_spans": [] }
1806.07336
Neural Code Comprehension: A Learnable Representation of Code Semantics
[ "Tal Ben-Nun", "Alice Shoshana Jakobovits", "Torsten Hoefler" ]
[ "cs.LG", "cs.NE", "cs.PL", "stat.ML" ]
2,018
en
Computer Science
[ -0.0691608116030693, 0.02708747424185276, -0.022738218307495117, 0.026751741766929626, -0.038731273263692856, 0.011056267656385899, 0.04156973585486412, -0.0060698832385241985, -0.007626459468156099, 0.010804468765854836, -0.030093802139163017, -0.0167560838162899, -0.011590386740863323, 0...
e61b5ed15d3138b4f808d207f4049d24915b9035
subsection
7
16
A Robust Distributional Hypothesis of Code
The linguistic Distributional Hypothesis , is given by: Words that occur in the same contexts tend to have similar meanings. We stipulate that code, which describes a sequence of operations to a processor, behaves similarly, and paraphrase this hypothesis to:Statements that occur in the same contexts tend to have simil...
{ "cite_spans": [] }
1806.07336
Neural Code Comprehension: A Learnable Representation of Code Semantics
[ "Tal Ben-Nun", "Alice Shoshana Jakobovits", "Torsten Hoefler" ]
[ "cs.LG", "cs.NE", "cs.PL", "stat.ML" ]
2,018
en
Computer Science
[ -0.01719984970986843, 0.006444220431149006, -0.028981823474168777, 0.010576304979622364, -0.011316494084894657, -0.04285464063286781, -0.005837570875883102, 0.03607847914099693, 0.003575035370886326, 0.009218020364642143, -0.03146946802735329, -0.020969470962882042, -0.02750144526362419, 0...
944d4398ff6eab3f0d8562a5311bd7fdbd1b5621
subsection
8
16
Statements
To choose the right abstraction for statements, we take two concerns into account: universality and uniformity. As stated above, source code comes in many languages and thus fixating on a single one would hinder universality. At the other extreme, machine code (assembly) is target-specific, containing specialized instr...
{ "cite_spans": [] }
1806.07336
Neural Code Comprehension: A Learnable Representation of Code Semantics
[ "Tal Ben-Nun", "Alice Shoshana Jakobovits", "Torsten Hoefler" ]
[ "cs.LG", "cs.NE", "cs.PL", "stat.ML" ]
2,018
en
Computer Science
[ -0.01445028092712164, 0.0034790539648383856, -0.06088344380259514, 0.06402679532766342, -0.01849391870200634, -0.07397567480802536, -0.017914075404405594, 0.027344143018126488, 0.0337834432721138, 0.0017805355601012707, -0.018203996121883392, -0.011268777772784233, -0.012901491485536098, -...
8d23ea98f9f8a02272d8a46c105a21b2f4aecc6a
subsection
9
16
Context
The definition of a context for code statements should also be carefully considered. We define context as statements whose execution directly depends on each other. Learning from consecutive statements in code does not necessarily fulfill this definition, as, for example, a programmer may use a variable in the first li...
{ "cite_spans": [] }
1806.07336
Neural Code Comprehension: A Learnable Representation of Code Semantics
[ "Tal Ben-Nun", "Alice Shoshana Jakobovits", "Torsten Hoefler" ]
[ "cs.LG", "cs.NE", "cs.PL", "stat.ML" ]
2,018
en
Computer Science
[ 0.00277351145632565, -0.008690590038895607, -0.03882152959704399, 0.030184349045157433, -0.028963547199964523, -0.020921507850289345, 0.00976642221212387, 0.03628836199641228, 0.006260429508984089, 0.005264712031930685, -0.016770778223872185, -0.035983163863420486, -0.024736516177654266, 0...
e39e6f1a6e2fda9f4e1269bcc9a02894e8081295
subsection
10
16
Similarity
To define similarity, one first needs to define the semantics of a statement. We draw the definition of semantics from Operational Semantics in programming language theory, which refers to the effects (e.g., preconditions, postconditions) of each computational step in a given program. In this paper, we specifically ass...
{ "cite_spans": [] }
1806.07336
Neural Code Comprehension: A Learnable Representation of Code Semantics
[ "Tal Ben-Nun", "Alice Shoshana Jakobovits", "Torsten Hoefler" ]
[ "cs.LG", "cs.NE", "cs.PL", "stat.ML" ]
2,018
en
Computer Science
[ 0.0029338959138840437, -0.0014307035598903894, -0.04859050735831261, 0.025409294292330742, -0.018313005566596985, -0.04907885193824768, 0.02400529757142067, 0.03867096081376076, 0.027561072260141373, -0.012254452332854271, -0.037236444652080536, -0.024753078818321228, -0.0003746058791875839,...
f7df941dc0ec5adebb7f1f3d757fea1bf8828ca1
subsection
11
16
Contextual Flow Processing
The aforementioned statements and contexts cannot be directly extracted from source code, but rather require processing akin to partial compilation (e.g., dataflow extraction). In this section, we briefly describe a popular compilation pipeline and proposed modifications to create a learnable vocabulary of statements a...
{ "cite_spans": [] }
1806.07336
Neural Code Comprehension: A Learnable Representation of Code Semantics
[ "Tal Ben-Nun", "Alice Shoshana Jakobovits", "Torsten Hoefler" ]
[ "cs.LG", "cs.NE", "cs.PL", "stat.ML" ]
2,018
en
Computer Science
[ 0.019933419302105904, 0.012790356762707233, -0.027000168338418007, 0.02944224141538143, -0.011958525516092777, -0.08284732699394226, 0.01197378896176815, 0.04322469234466553, -0.0021520766895264387, 0.017079247161746025, -0.01011933945119381, -0.030022233724594116, -0.029213298112154007, 0...
338d9b08ea3572e55d69005c6b2b7c1692fa9f4c
subsection
12
16
Compilation, Static Single Assignment, and LLVM IR
Major contemporary compilers, such as GCC and LLVM, support multiple programming languages and hardware targets. To avoid duplication in code optimization techniques, they enforce a strict separation between the source language (frontend), an Intermediate Representation (IR) that can be optimized, and the target machin...
{ "cite_spans": [] }
1806.07336
Neural Code Comprehension: A Learnable Representation of Code Semantics
[ "Tal Ben-Nun", "Alice Shoshana Jakobovits", "Torsten Hoefler" ]
[ "cs.LG", "cs.NE", "cs.PL", "stat.ML" ]
2,018
en
Computer Science
[ -0.08085650950670242, 0.01794099062681198, -0.01638488471508026, 0.034753043204545975, -0.02392132207751274, -0.008345001377165318, -0.029535509645938873, 0.0037243575789034367, 0.042167432606220245, 0.027247117832303047, -0.020687060430645943, -0.0005740048945881426, 0.020763341337442398, ...
8e7d2ecd1033f653f00ee101e9c92f98353b5ef8
subsection
13
16
Contextual Flow Graphs
To analyze dataflow for optimization, LLVM divides the IR statements into “basic blocks”, which contain no control-flow divergence, illustrated in Fig. REF . Within a basic block, statements naturally create traceable dataflow as SSA lists data dependencies in the form of input identifiers (even if conditional), and as...
{ "cite_spans": [] }
1806.07336
Neural Code Comprehension: A Learnable Representation of Code Semantics
[ "Tal Ben-Nun", "Alice Shoshana Jakobovits", "Torsten Hoefler" ]
[ "cs.LG", "cs.NE", "cs.PL", "stat.ML" ]
2,018
en
Computer Science
[ -0.030557233840227127, 0.003655573120340705, -0.03675415366888046, 0.030725130811333656, -0.01950656622648239, -0.018911294639110565, -0.038036275655031204, -0.01886550523340702, 0.030496180057525635, 0.010997246019542217, -0.005559676326811314, -0.011737518943846226, -0.0011151788057759404,...
3f94cdc66f825c66e834a4fcc710efcc54b2fae7
subsection
14
16
Body
With XFGs providing a notion of context, we can now train an embedding space for individual statements. To support learnability, desiderata for such a space include: (a) statements that are in close proximity should have similar artifacts on a system (i.e., use the same resources); and (b) changing the same attributes ...
{ "cite_spans": [] }
1806.07336
Neural Code Comprehension: A Learnable Representation of Code Semantics
[ "Tal Ben-Nun", "Alice Shoshana Jakobovits", "Torsten Hoefler" ]
[ "cs.LG", "cs.NE", "cs.PL", "stat.ML" ]
2,018
en
Computer Science
[ -0.0670652985572815, -0.012059854343533516, -0.012830281630158424, -0.006861378438770771, -0.01920728199183941, -0.04000118747353554, -0.007151241879910231, -0.020519297569990158, 0.033502139151096344, -0.019558170810341835, -0.02198387123644352, -0.02212117426097393, 0.001557063776999712, ...
2820e46d8576e7d4048af62a2ecc4a9e1b60956b
subsection
15
16
Preprocessing
First, we filter out comments and metadata from statements. Then, identifiers and immediate values (numeric constants, strings) are replaced with %ID and <INT/FLOAT/STRING> respectively, where immediate values are fed separately to downstream RNNs. Lastly, data structures are “inlined”, that is, their contents are enco...
{ "cite_spans": [] }
1806.07336
Neural Code Comprehension: A Learnable Representation of Code Semantics
[ "Tal Ben-Nun", "Alice Shoshana Jakobovits", "Torsten Hoefler" ]
[ "cs.LG", "cs.NE", "cs.PL", "stat.ML" ]
2,018
en
Computer Science
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d3b501aeefdba57581dfeaf0074308926ff8eb66
abstract
0
58
Abstract
Let $G$ be a linearly reductive group acting on a vector space $V$, and $f$ a (semi-)invariant polynomial on $V$. In this paper we study systematically decompositions of the Bernstein-Sato polynomial of $f$ in parallel with some representation-theoretic properties of the action of $G$ on $V$. We provide a technique bas...
{ "cite_spans": [] }
1802.07760
Decompositions of Bernstein-Sato polynomials and slices
[ "András Cristian Lőrincz" ]
[ "math.RT" ]
2,018
en
Mathematics
[ -0.023692820221185684, 0.005637152120471001, -0.015340072102844715, 0.013951760716736317, 0.02209092304110527, -0.02840697579085827, 0.040032170712947845, 0.03929987549781799, 0.005881250835955143, 0.05403732880949974, -0.021129785105586052, 0.029230808839201927, -0.004756108857691288, -0....
6e481088c743d9185d7d3419682b0626e976ed48
subsection
1
58
Introduction
The classification of irreducible prehomogeneous vector spaces was achieved in . The computation of b-functions (i.e. Bernstein-Sato polynomials) of their semi-invariants has been completed using sophisticated methods such as microlocal calculus (for example, see , ). Extensive calculations have been done also in the c...
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1802.07760
Decompositions of Bernstein-Sato polynomials and slices
[ "András Cristian Lőrincz" ]
[ "math.RT" ]
2,018
en
Mathematics
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6c63263399cb7ce08fe458a80a49c650e32dbdf5
subsection
2
58
Introduction
In Section we explain how one can use the technique based on the multiplicity one property to derive this result in an elementary way.A simple, yet non-trivial example of interest is the following semi-invariant, coming from the quiver 4:\det \begin{pmatrix} X & Y & 0 \\ 0 & Y & Z \end{pmatrix}.Here X,Y,Z are generic m...
{ "cite_spans": [] }
1802.07760
Decompositions of Bernstein-Sato polynomials and slices
[ "András Cristian Lőrincz" ]
[ "math.RT" ]
2,018
en
Mathematics
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3d8bec343d337135ed954e5b9cad57154d9cf502
subsection
3
58
Introduction
Then for any l-tuple (d_1,\dots ,d_l), we use the following notation in \mathbb {C}[s_1,\dots ,s_l]:[s]^{d_1,\dots ,d_l}_{a,b}=\prod _{i=a+1}^b \prod _{j=0}^{d-1} (d_1s_1+\dots +d_ls_l+i+j),where d=m_1d_1+\dots + m_ld_l.
{ "cite_spans": [] }
1802.07760
Decompositions of Bernstein-Sato polynomials and slices
[ "András Cristian Lőrincz" ]
[ "math.RT" ]
2,018
en
Mathematics
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eac8afa4f1e7e1620080e87062c3092eb26fad87
subsection
4
58
Definition
First we define and briefly recall some basic properties about Bernstein-Sato polynomials. We will interchangeably call them also b-functions, especially in the contexts of Theorem REF and Lemma REF from Section REF . For details on Bernstein-Sato polynomials, we refer the reader to , .Throughout this paper we work ove...
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1802.07760
Decompositions of Bernstein-Sato polynomials and slices
[ "András Cristian Lőrincz" ]
[ "math.RT" ]
2,018
en
Mathematics
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34f0d655adfbef957b0deae72ad3f923b1cba5a6
subsection
5
58
Body
Let G be a (connected) reductive algebraic group, acting rationally on V. That is, we have a morphism of algebraic groups \rho : G \rightarrow \operatorname{GL}(V). Then we have an action of G on \mathbb {C}[V] by (g\cdot f)(v)=f(g^{-1}\cdot v) for all v\in V, where g\in G, f\in \mathbb {C}[V]. We call a polynomial f\i...
{ "cite_spans": [ { "arxiv_id": "", "doi": "10.1016/j.jalgebra.2017.03.028", "end": 1249, "openalex_id": "https://openalex.org/W2963471102", "raw": ", The b-functions of semi-invariants of quivers, J. Algebra 482 (2017), 346–363.", "source_ref_id": "d64af415bb8e334e64e24dd0a58b...
1802.07760
Decompositions of Bernstein-Sato polynomials and slices
[ "András Cristian Lőrincz" ]
[ "math.RT" ]
2,018
en
Mathematics
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c2269fe077c897c23908fbd7cddc926f7cdf6de4
subsection
6
58
Body
We have the \operatorname{GL}(V)-equivariant pairing between \mathbb {C}[V]_d and \mathbb {C}[V^*]_d by\langle P,P^*\rangle = P^*(\partial x) \cdot P(x).This gives a \operatorname{GL}(V)-equivariant isomorphism \mathbb {C}[V^*]_d \cong (\mathbb {C}[V]_d)^*.Let f\in \mathbb {C}[V] be a semi-invariant of weight \sigma , ...
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1802.07760
Decompositions of Bernstein-Sato polynomials and slices
[ "András Cristian Lőrincz" ]
[ "math.RT" ]
2,018
en
Mathematics
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74a9e66c3e23047bc39e4c5f1aff05d6ae6d70f4
subsection
7
58
Body
Assume that the product \sigma _1\cdots \sigma _l is a multiplicity-free weight in \mathbb {C}[V]. In this case we can take respective dual semi-invariants f^*_1,\dots , f^*_l\in \mathbb {C}[V^*]. Put \underline{f}=(f_1,\dots , f_l) and \underline{f}^*=(f_1^*,\dots , f_l^*). For a multi-variable \underline{s}=(s_1,\dot...
{ "cite_spans": [] }
1802.07760
Decompositions of Bernstein-Sato polynomials and slices
[ "András Cristian Lőrincz" ]
[ "math.RT" ]
2,018
en
Mathematics
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9b01288b4c8e9d4a9c50027a0a6e8fe8dc596ad3
subsection
8
58
Bernstein-Sato polynomials of ideals
Now we consider tuples of polynomials \underline{f}=(f_1,\dots ,f_r) with f_i \in \mathbb {C}[V], from a different viewpoint. Following , we introduce (note that in the case of r=1 we recover Definition REF ):Definition 1.5 A tuple \underline{f}= (f_1,\dots ,f_r) in \mathbb {C}[V] is said to be a multiplicity-free tup...
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1802.07760
Decompositions of Bernstein-Sato polynomials and slices
[ "András Cristian Lőrincz" ]
[ "math.RT" ]
2,018
en
Mathematics
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183e96df26be6b1db9ed109a3e44f2f628532ea0
subsection
9
58
Bernstein-Sato polynomials of ideals
If we let s=s_1+\dots +s_r then there exists a polynomial P_f(s)\in \mathbb {C}[s] such thatD_{\underline{f}}\cdot \underline{f}^{\underline{s}} = P_{\underline{f}}(s)\cdot \underline{f}^{\underline{s}},and the Bernstein-Sato polynomial b_{\underline{f}}(s) divides P_{\underline{f}}(s).As in the case r=1 (by Theorem RE...
{ "cite_spans": [ { "arxiv_id": "", "doi": "", "end": 589, "openalex_id": "", "raw": "A. Lőrincz, C. Raicu, J. Weyman, and U. Walther, Bernstein-Sato polynomials for maximal minors and sub-maximal Pfaffians, Adv. Math. 307 (2017), 224–252.", "source_ref_id": "44b04b084a190987ab...
1802.07760
Decompositions of Bernstein-Sato polynomials and slices
[ "András Cristian Lőrincz" ]
[ "math.RT" ]
2,018
en
Mathematics
[ 0.003260530298575759, 0.01657547429203987, -0.048627499490976334, -0.013843421824276447, -0.003333028871566057, -0.041728682816028595, 0.05918940156698227, 0.042919185012578964, 0.027778420597314835, 0.02738158591091633, -0.051710598170757294, 0.033578310161828995, -0.02275693602859974, -0...
416c4512cbcb91a7ab46052075b9c69bed7b8dec
subsection
10
58
Slices and the multiplicity one property
In this section, we develop several techniques for calculating b-functions. These are similar to the methods used in , , . The slice method developed in Section REF will be used further in Section .
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1802.07760
Decompositions of Bernstein-Sato polynomials and slices
[ "András Cristian Lőrincz" ]
[ "math.RT" ]
2,018
en
Mathematics
[ -0.026893220841884613, 0.017521802335977554, -0.014743956737220287, 0.01828494854271412, -0.003577240975573659, 0.04337714612483978, 0.04871916025876999, 0.018071267753839493, -0.004464396741241217, 0.027229003608226776, -0.014217386022210121, 0.02738163247704506, 0.014507381245493889, 0.0...
425283167f8b1cb49e7e82d3b8b8fc583013222f
subsection
11
58
Slices
Let H be a connected affine algebraic group and V a rational H-module. Let f\in \mathbb {C}[V] be a non-zero H-semi-invariant of weight \sigma . Denote by \mathfrak {h} the Lie algebra of H. Fix an element v\in V and let H_v be the stabilizer of v. The tangent space at v to the orbit \mathcal {O}=G\cdot v of v is T_v(\...
{ "cite_spans": [ { "arxiv_id": "", "doi": "10.2307/2372490", "end": 521, "openalex_id": "https://openalex.org/W2328147349", "raw": "G. D. Mostow, Fully reducible subgroups of algebraic groups, Amer. J. Math. 78 (1956), no. 1, 200–221.", "source_ref_id": "78781959dbf2b425792cdb...
1802.07760
Decompositions of Bernstein-Sato polynomials and slices
[ "András Cristian Lőrincz" ]
[ "math.RT" ]
2,018
en
Mathematics
[ -0.0013052342692390084, 0.02686360850930214, 0.005846381653100252, 0.012547029182314873, 0.04969996586441994, -0.036428336054086685, 0.01572764292359352, 0.02704666554927826, 0.06181223317980766, 0.03307228907942772, 0.002597120590507984, -0.009473197162151337, 0.019419291988015175, 0.0176...
98e54f314d59e01fb3567d99780133a7aa051153
subsection
12
58
Expansions and the multiplicity one property
We recall and generalize some considerations from . Let G be a (connected) reductive group with a Borel subgroup B that contains a maximal torus T. The irreducible rational G-modules are parameterized by dominant T-weights. Let V an algebraic G-module, and fix f\in \operatorname{SI}(G,V)_\sigma with \sigma multiplicity...
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1802.07760
Decompositions of Bernstein-Sato polynomials and slices
[ "András Cristian Lőrincz" ]
[ "math.RT" ]
2,018
en
Mathematics
[ -0.03423342853784561, 0.005491994321346283, -0.004870330914855003, -0.0040312763303518295, 0.024256307631731033, -0.0432036854326725, 0.03618614003062248, -0.00818459689617157, 0.07176205515861511, 0.03923724591732025, -0.025736095383763313, -0.008039669133722782, -0.025080107152462006, 0....
79b9907c6b764d98a8a0b3c00c644b30aeea554b
subsection
13
58
Expansions and the multiplicity one property
Geometrically, if f_1^{(1)},\dots , f_p^{(1)} generate the (reduced) defining ideal of a closed subset of the zero-set Z(f), then we have an expansion (REF ) as above.Example 2.4 The case considered in is when V is reducible, that is, there is a non-trivial G-decomposition V=E\oplus F. Then \mathbb {C}[V]=\mathbb {C}[...
{ "cite_spans": [ { "arxiv_id": "", "doi": "10.1142/s0129167x0600345x", "end": 382, "openalex_id": "https://openalex.org/W2145362545", "raw": "F. Sato and K. Sugiyama, Multiplicity one property and the decomposition of b-functions, Internat. J. Math. 17 (2006), 195–229.", "sour...
1802.07760
Decompositions of Bernstein-Sato polynomials and slices
[ "András Cristian Lőrincz" ]
[ "math.RT" ]
2,018
en
Mathematics
[ -0.05549023300409317, 0.004669969901442528, -0.0007044062367640436, 0.019366640597581863, 0.025257516652345657, -0.0463334284722805, 0.03690192103385925, 0.02780616097152233, 0.04132770746946335, 0.04547879099845886, -0.0594276562333107, -0.023883996531367302, -0.01268980372697115, 0.01944...
7c344c97666d3cb4d0eb01bb612a3e2be89f495f
subsection
14
58
Expansions and the multiplicity one property
N_{\lambda \cdot \sigma ^{-1}}) that is G-dual to f_1^{(1)},\dots , f_p^{(1)} (resp. f_1^{(2)},\dots ,f_p^{(2)}) with respect to the pairing REF .As in , we assume that the following multiplicity one property is satisfied: \mathbb {C}[V]_{\lambda \cdot \sigma ^{d-k-1}}=M_\lambda \cdot f^{d-k-1}, or equivalently:\mbox{T...
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1802.07760
Decompositions of Bernstein-Sato polynomials and slices
[ "András Cristian Lőrincz" ]
[ "math.RT" ]
2,018
en
Mathematics
[ -0.03341641277074814, 0.02171303890645504, -0.008758457377552986, -0.004104573279619217, 0.02650425210595131, -0.012771478854119778, 0.03933676332235336, 0.045135047286748886, 0.028213217854499817, 0.0245816633105278, -0.03951986879110336, 0.016235189512372017, 0.008796603418886662, 0.0118...
1585b34f41f432e47059971f27bce5b5f91daeec
subsection
15
58
Expansions and the multiplicity one property
Clearly, -1 is a root of b_2(s), and b_1(s) satisfies\left(\displaystyle \sum _{i=1}^n \partial _{i} x_{i}\right) \cdot f^s = b_{1}(s) \cdot f^s.The operator on the LHS equals E+n, where E denotes the usual Euler operator. Hence, we have b_1(s)=ds+n, proving our claim.We note that for all irreducible prehomogeneous spa...
{ "cite_spans": [ { "arxiv_id": "", "doi": "", "end": 491, "openalex_id": "", "raw": "T. Kimura, The b-functions and holonomy diagrams of irreducible regular prehomogeneous vector spaces, Nagoya Math. J. 85 (1982), 1–80.", "source_ref_id": "4019a9fd98b65937e5ca2c9bfb53165b03715...
1802.07760
Decompositions of Bernstein-Sato polynomials and slices
[ "András Cristian Lőrincz" ]
[ "math.RT" ]
2,018
en
Mathematics
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e7b259ca0dca7b66d0388d94f708db2120ab4ede
subsection
16
58
Examples of irreducible prehomogeneous spaces
As explained in , the decomposition technique as in Example REF can be used to obtain in an elementary way the b-functions of some classical (semi-)invariants such as the determinant and the Pfaffian. Previous proofs rely on sophisticated methods such as Capelli's identity (see , ) or microlocal calculus (see ). Howeve...
{ "cite_spans": [ { "arxiv_id": "", "doi": "10.1142/s0129167x0600345x", "end": 201, "openalex_id": "https://openalex.org/W2145362545", "raw": "F. Sato and K. Sugiyama, Multiplicity one property and the decomposition of b-functions, Internat. J. Math. 17 (2006), 195–229.", "sour...
1802.07760
Decompositions of Bernstein-Sato polynomials and slices
[ "András Cristian Lőrincz" ]
[ "math.RT" ]
2,018
en
Mathematics
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14d567d1cf094c6f16ada1b4068fcdbbdfc27a1d
subsection
17
58
Examples of irreducible prehomogeneous spaces
By Theorem REF , the b-function of f decomposes as b_n(s)=b_{k,1}(s)\cdot b_{k,2}(s), and for any i=1,\dots ,p we have the equation\left(\dfrac{1}{f^{(1)}_i (x)} \, f^{*(2)}_i(\partial x) \right) \cdot f^{s+1}(x) = b_{k,2}(s) f^s(x).We can choose f_1^{(1)} (resp. f_1^{*(2)}) to be k\times k (resp. (n-k) \times (n-k)) m...
{ "cite_spans": [] }
1802.07760
Decompositions of Bernstein-Sato polynomials and slices
[ "András Cristian Lőrincz" ]
[ "math.RT" ]
2,018
en
Mathematics
[ -0.008187344297766685, 0.03686975687742233, -0.029254687950015068, -0.03320719674229622, 0.012200898490846157, 0.022265303879976273, 0.05976074934005737, 0.020601892843842506, 0.03833477944135666, 0.042577244341373444, -0.011636254377663136, 0.017244547605514526, 0.005180994514375925, -0.0...
188415f7e74d56c679c53738e7ae3d7c4ddb02ba
subsection
18
58
Examples of irreducible prehomogeneous spaces
By Lemma REF , we have b_{f,\mathcal {O}_k}=b_{f,v}(s) = b_{f_v}(s)=b_{n-k}(s), hence obtaining the desired equality. We will exploit techniques with slices more systematically in the next section.Example 2.9 (\operatorname{SO}(m)\times \operatorname{GL}(n), \Lambda _1 \otimes \Lambda _1), where m>n.This example is als...
{ "cite_spans": [ { "arxiv_id": "", "doi": "10.1007/bf01391666", "end": 369, "openalex_id": "https://openalex.org/W1983716288", "raw": "M. Sato, M. Kashiwara, T. Kimura, and T. Oshima, Micro-local analysis of prehomogeneous vector spaces, Invent. Math. 62 (1980), 117–179.", "so...
1802.07760
Decompositions of Bernstein-Sato polynomials and slices
[ "András Cristian Lőrincz" ]
[ "math.RT" ]
2,018
en
Mathematics
[ -0.045728400349617004, 0.022070517763495445, -0.013408678583800793, -0.03550209105014801, 0.04609471559524536, 0.025229988619685173, 0.010218679904937744, 0.04850629344582558, 0.013752099126577377, 0.014927362091839314, -0.02822156623005867, 0.011371048167347908, 0.003813880030065775, 0.02...
87175b911d12bd6c1ca420796f79ad58dd5645e9
subsection
19
58
Examples of irreducible prehomogeneous spaces
Specializing the equation above atX=\begin{bmatrix} I_r & X_r\\ 0 & X_{n-r} \end{bmatrix},and simplifying f_{m,n}, we obtain precisely the equation for the b-function of the semi-invariant f_{m-r,n-r} in the variables of X_{n-r}. Hence b^{\prime }_{r,2}(s)=b_{m-r,n-r}(s), and we have a decompositionb_{m,n}(s) = b^{\pri...
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1802.07760
Decompositions of Bernstein-Sato polynomials and slices
[ "András Cristian Lőrincz" ]
[ "math.RT" ]
2,018
en
Mathematics
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3136ae884c9ab13854797d82b23167a61f15d381
subsection
20
58
Examples of irreducible prehomogeneous spaces
Putting r=1, we obtainb_{m,n}(s) =(s+2n-1)(s+2m)\cdot b_{m-1,n-1}(s) = \prod _{i=1}^n \left(s+ 2i-1\right)\left(s+2(m-n+i) \right).Example 2.11 (\operatorname{GL}(2), 3\Lambda _1), the space of binary cubics.This example appears also in . Here V=\operatorname{Sym}^3 \mathbb {C}^2 is the space of binary cubic forms with...
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1802.07760
Decompositions of Bernstein-Sato polynomials and slices
[ "András Cristian Lőrincz" ]
[ "math.RT" ]
2,018
en
Mathematics
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437630fbc7dd728c0a8357de3300d08c265c9189
subsection
21
58
Examples of irreducible prehomogeneous spaces
Hence (REF ) holds, and by Theorem REF we have a decomposition b(s) = b_{2,1}(s) \cdot b_{2,2}(s). We give more details for this case. A basis of M_\lambda =M_{\lambda ^*\cdot \sigma } (resp. basis of N_{\lambda ^*}=N_{\lambda \cdot \sigma ^{-1}}) is given by the 2\times 2 minors of\begin{bmatrix} x_0 & x_1 & x_2\\ x_1...
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1802.07760
Decompositions of Bernstein-Sato polynomials and slices
[ "András Cristian Lőrincz" ]
[ "math.RT" ]
2,018
en
Mathematics
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65ed6a15193fa71292c6cd599491b341c3e438ce
subsection
22
58
Examples of irreducible prehomogeneous spaces
Using this, it is easy to see that the multiplicity one property (REF ) holds for all cases k=1,2,3, just as in the above example. Hence one can apply Theorem REF here as well and obtain decompositions of the b-function of f.
{ "cite_spans": [] }
1802.07760
Decompositions of Bernstein-Sato polynomials and slices
[ "András Cristian Lőrincz" ]
[ "math.RT" ]
2,018
en
Mathematics
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