authors stringlengths 31 2.94k | categories stringclasses 918
values | comment stringlengths 1 491 ⌀ | doi stringlengths 13 97 ⌀ | entry_id stringlengths 32 39 | journal_ref stringlengths 8 396 ⌀ | pdf_url stringlengths 32 39 | primary_category stringclasses 51
values | published stringdate 1993-08-01 00:00:00 2023-06-27 17:57:34 | summary stringlengths 25 3.66k | title stringlengths 4 252 | updated stringdate 1993-08-01 00:00:00 2023-06-27 17:57:34 |
|---|---|---|---|---|---|---|---|---|---|---|---|
[arxiv.Result.Author('M. L. Ginsberg')] | ['cs.AI'] | See http://www.jair.org/ for an online appendix and other files
accompanying this article | null | http://arxiv.org/abs/cs/9308101v1 | Journal of Artificial Intelligence Research, Vol 1, (1993), 25-46 | http://arxiv.org/pdf/cs/9308101v1 | cs.AI | 1993-08-01 00:00:00+00:00 | Because of their occasional need to return to shallow points in a search
tree, existing backtracking methods can sometimes erase meaningful progress
toward solving a search problem. In this paper, we present a method by which
backtrack points can be moved deeper in the search space, thereby avoiding this
difficulty. Th... | Dynamic Backtracking | 1993-08-01 00:00:00+00:00 |
[arxiv.Result.Author('M. P. Wellman')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9308102v1 | Journal of Artificial Intelligence Research, Vol 1, (1993), 1-23 | http://arxiv.org/pdf/cs/9308102v1 | cs.AI | 1993-08-01 00:00:00+00:00 | Market price systems constitute a well-understood class of mechanisms that
under certain conditions provide effective decentralization of decision making
with minimal communication overhead. In a market-oriented programming approach
to distributed problem solving, we derive the activities and resource
allocations for a... | A Market-Oriented Programming Environment and its Application to Distributed Multicommodity Flow Problems | 1993-08-01 00:00:00+00:00 |
[arxiv.Result.Author('I. P. Gent'), arxiv.Result.Author('T. Walsh')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9309101v1 | Journal of Artificial Intelligence Research, Vol 1, (1993), 47-59 | http://arxiv.org/pdf/cs/9309101v1 | cs.AI | 1993-09-01 00:00:00+00:00 | We describe an extensive study of search in GSAT, an approximation procedure
for propositional satisfiability. GSAT performs greedy hill-climbing on the
number of satisfied clauses in a truth assignment. Our experiments provide a
more complete picture of GSAT's search than previous accounts. We describe in
detail the t... | An Empirical Analysis of Search in GSAT | 1993-09-01 00:00:00+00:00 |
[arxiv.Result.Author('F. Bergadano'), arxiv.Result.Author('D. Gunetti'), arxiv.Result.Author('U. Trinchero')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9311101v1 | Journal of Artificial Intelligence Research, Vol 1, (1993), 91-107 | http://arxiv.org/pdf/cs/9311101v1 | cs.AI | 1993-11-01 00:00:00+00:00 | As real logic programmers normally use cut (!), an effective learning
procedure for logic programs should be able to deal with it. Because the cut
predicate has only a procedural meaning, clauses containing cut cannot be
learned using an extensional evaluation method, as is done in most learning
systems. On the other h... | The Difficulties of Learning Logic Programs with Cut | 1993-11-01 00:00:00+00:00 |
[arxiv.Result.Author('J. C. Schlimmer'), arxiv.Result.Author('L. A. Hermens')] | ['cs.AI'] | See http://www.jair.org/ for an online appendix and other files
accompanying this article | null | http://arxiv.org/abs/cs/9311102v1 | Journal of Artificial Intelligence Research, Vol 1, (1993), 61-89 | http://arxiv.org/pdf/cs/9311102v1 | cs.AI | 1993-11-01 00:00:00+00:00 | To support the goal of allowing users to record and retrieve information,
this paper describes an interactive note-taking system for pen-based computers
with two distinctive features. First, it actively predicts what the user is
going to write. Second, it automatically constructs a custom, button-box user
interface on ... | Software Agents: Completing Patterns and Constructing User Interfaces | 1993-11-01 00:00:00+00:00 |
[arxiv.Result.Author('M. Buchheit'), arxiv.Result.Author('F. M. Donini'), arxiv.Result.Author('A. Schaerf')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9312101v1 | Journal of Artificial Intelligence Research, Vol 1, (1993),
109-138 | http://arxiv.org/pdf/cs/9312101v1 | cs.AI | 1993-12-01 00:00:00+00:00 | Terminological knowledge representation systems (TKRSs) are tools for
designing and using knowledge bases that make use of terminological languages
(or concept languages). We analyze from a theoretical point of view a TKRS
whose capabilities go beyond the ones of presently available TKRSs. The new
features studied, oft... | Decidable Reasoning in Terminological Knowledge Representation Systems | 1993-12-01 00:00:00+00:00 |
[arxiv.Result.Author('N. Nilsson')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9401101v1 | Journal of Artificial Intelligence Research, Vol 1, (1994),
139-158 | http://arxiv.org/pdf/cs/9401101v1 | cs.AI | 1994-01-01 00:00:00+00:00 | A formalism is presented for computing and organizing actions for autonomous
agents in dynamic environments. We introduce the notion of teleo-reactive (T-R)
programs whose execution entails the construction of circuitry for the
continuous computation of the parameters and conditions on which agent action
is based. In a... | Teleo-Reactive Programs for Agent Control | 1994-01-01 00:00:00+00:00 |
[arxiv.Result.Author('C. X. Ling')] | ['cs.AI'] | See http://www.jair.org/ for an online appendix and other files
accompanying this article | null | http://arxiv.org/abs/cs/9402101v1 | Journal of Artificial Intelligence Research, Vol 1, (1994),
209-229 | http://arxiv.org/pdf/cs/9402101v1 | cs.AI | 1994-02-01 00:00:00+00:00 | Learning the past tense of English verbs - a seemingly minor aspect of
language acquisition - has generated heated debates since 1986, and has become
a landmark task for testing the adequacy of cognitive modeling. Several
artificial neural networks (ANNs) have been implemented, and a challenge for
better symbolic model... | Learning the Past Tense of English Verbs: The Symbolic Pattern Associator vs. Connectionist Models | 1994-02-01 00:00:00+00:00 |
[arxiv.Result.Author('D. J. Cook'), arxiv.Result.Author('L. B. Holder')] | ['cs.AI'] | See http://www.jair.org/ for an online appendix and other files
accompanying this article | null | http://arxiv.org/abs/cs/9402102v1 | Journal of Artificial Intelligence Research, Vol 1, (1994),
231-255 | http://arxiv.org/pdf/cs/9402102v1 | cs.AI | 1994-02-01 00:00:00+00:00 | The ability to identify interesting and repetitive substructures is an
essential component to discovering knowledge in structural data. We describe a
new version of our SUBDUE substructure discovery system based on the minimum
description length principle. The SUBDUE system discovers substructures that
compress the ori... | Substructure Discovery Using Minimum Description Length and Background Knowledge | 1994-02-01 00:00:00+00:00 |
[arxiv.Result.Author('M. Koppel'), arxiv.Result.Author('R. Feldman'), arxiv.Result.Author('A. M. Segre')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9402103v1 | Journal of Artificial Intelligence Research, Vol 1, (1994),
159-208 | http://arxiv.org/pdf/cs/9402103v1 | cs.AI | 1994-02-01 00:00:00+00:00 | The theory revision problem is the problem of how best to go about revising a
deficient domain theory using information contained in examples that expose
inaccuracies. In this paper we present our approach to the theory revision
problem for propositional domain theories. The approach described here, called
PTR, uses pr... | Bias-Driven Revision of Logical Domain Theories | 1994-02-01 00:00:00+00:00 |
[arxiv.Result.Author('P. M. Murphy'), arxiv.Result.Author('M. J. Pazzani')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9403101v1 | Journal of Artificial Intelligence Research, Vol 1, (1994),
257-275 | http://arxiv.org/pdf/cs/9403101v1 | cs.AI | 1994-03-01 00:00:00+00:00 | We report on a series of experiments in which all decision trees consistent
with the training data are constructed. These experiments were run to gain an
understanding of the properties of the set of consistent decision trees and the
factors that affect the accuracy of individual trees. In particular, we
investigated t... | Exploring the Decision Forest: An Empirical Investigation of Occam's Razor in Decision Tree Induction | 1994-03-01 00:00:00+00:00 |
[arxiv.Result.Author('A. Borgida'), arxiv.Result.Author('P. F. Patel-Schneider')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9406101v1 | Journal of Artificial Intelligence Research, Vol 1, (1994),
277-308 | http://arxiv.org/pdf/cs/9406101v1 | cs.AI | 1994-06-01 00:00:00+00:00 | This paper analyzes the correctness of the subsumption algorithm used in
CLASSIC, a description logic-based knowledge representation system that is
being used in practical applications. In order to deal efficiently with
individuals in CLASSIC descriptions, the developers have had to use an
algorithm that is incomplete ... | A Semantics and Complete Algorithm for Subsumption in the CLASSIC Description Logic | 1994-06-01 00:00:00+00:00 |
[arxiv.Result.Author('R. Sebastiani')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9406102v1 | Journal of Artificial Intelligence Research, Vol 1, (1994),
309-314 | http://arxiv.org/pdf/cs/9406102v1 | cs.AI | 1994-06-01 00:00:00+00:00 | In this paper we describe how to modify GSAT so that it can be applied to
non-clausal formulas. The idea is to use a particular ``score'' function which
gives the number of clauses of the CNF conversion of a formula which are false
under a given truth assignment. Its value is computed in linear time, without
constructi... | Applying GSAT to Non-Clausal Formulas | 1994-06-01 00:00:00+00:00 |
[arxiv.Result.Author('A. J. Grove'), arxiv.Result.Author('J. Y. Halpern'), arxiv.Result.Author('D. Koller')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9408101v1 | Journal of Artificial Intelligence Research, Vol 2, (1994), 33-88 | http://arxiv.org/pdf/cs/9408101v1 | cs.AI | 1994-08-01 00:00:00+00:00 | Given a knowledge base KB containing first-order and statistical facts, we
consider a principled method, called the random-worlds method, for computing a
degree of belief that some formula Phi holds given KB. If we are reasoning
about a world or system consisting of N individuals, then we can consider all
possible worl... | Random Worlds and Maximum Entropy | 1994-08-01 00:00:00+00:00 |
[arxiv.Result.Author('T. Kitani'), arxiv.Result.Author('Y. Eriguchi'), arxiv.Result.Author('M. Hara')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9408102v1 | Journal of Artificial Intelligence Research, Vol 2, (1994), 89-110 | http://arxiv.org/pdf/cs/9408102v1 | cs.AI | 1994-08-01 00:00:00+00:00 | Information extraction is the task of automatically picking up information of
interest from an unconstrained text. Information of interest is usually
extracted in two steps. First, sentence level processing locates relevant
pieces of information scattered throughout the text; second, discourse
processing merges corefer... | Pattern Matching and Discourse Processing in Information Extraction from Japanese Text | 1994-08-01 00:00:00+00:00 |
[arxiv.Result.Author('S. K. Murthy'), arxiv.Result.Author('S. Kasif'), arxiv.Result.Author('S. Salzberg')] | ['cs.AI'] | See http://www.jair.org/ for an online appendix and other files
accompanying this article | null | http://arxiv.org/abs/cs/9408103v1 | Journal of Artificial Intelligence Research, Vol 2, (1994), 1-32 | http://arxiv.org/pdf/cs/9408103v1 | cs.AI | 1994-08-01 00:00:00+00:00 | This article describes a new system for induction of oblique decision trees.
This system, OC1, combines deterministic hill-climbing with two forms of
randomization to find a good oblique split (in the form of a hyperplane) at
each node of a decision tree. Oblique decision tree methods are tuned
especially for domains i... | A System for Induction of Oblique Decision Trees | 1994-08-01 00:00:00+00:00 |
[arxiv.Result.Author('S. Safra'), arxiv.Result.Author('M. Tennenholtz')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9409101v1 | Journal of Artificial Intelligence Research, Vol 2, (1994),
111-129 | http://arxiv.org/pdf/cs/9409101v1 | cs.AI | 1994-09-01 00:00:00+00:00 | This paper introduces a framework for Planning while Learning where an agent
is given a goal to achieve in an environment whose behavior is only partially
known to the agent. We discuss the tractability of various plan-design
processes. We show that for a large natural class of Planning while Learning
systems, a plan c... | On Planning while Learning | 1994-09-01 00:00:00+00:00 |
[arxiv.Result.Author('S. Soderland'), arxiv.Result.Author('Lehnert. W')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9412101v1 | Journal of Artificial Intelligence Research, Vol 2, (1994),
131-158 | http://arxiv.org/pdf/cs/9412101v1 | cs.AI | 1994-12-01 00:00:00+00:00 | The vast amounts of on-line text now available have led to renewed interest
in information extraction (IE) systems that analyze unrestricted text,
producing a structured representation of selected information from the text.
This paper presents a novel approach that uses machine learning to acquire
knowledge for some of... | Wrap-Up: a Trainable Discourse Module for Information Extraction | 1994-12-01 00:00:00+00:00 |
[arxiv.Result.Author('W. L. Buntine')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9412102v1 | Journal of Artificial Intelligence Research, Vol 2, (1994),
159-225 | http://arxiv.org/pdf/cs/9412102v1 | cs.AI | 1994-12-01 00:00:00+00:00 | This paper is a multidisciplinary review of empirical, statistical learning
from a graphical model perspective. Well-known examples of graphical models
include Bayesian networks, directed graphs representing a Markov chain, and
undirected networks representing a Markov field. These graphical models are
extended to mode... | Operations for Learning with Graphical Models | 1994-12-01 00:00:00+00:00 |
[arxiv.Result.Author('S. Minton'), arxiv.Result.Author('J. Bresina'), arxiv.Result.Author('M. Drummond')] | ['cs.AI'] | See http://www.jair.org/ for an online appendix and other files
accompanying this article | null | http://arxiv.org/abs/cs/9412103v1 | Journal of Artificial Intelligence Research, Vol 2, (1994),
227-262 | http://arxiv.org/pdf/cs/9412103v1 | cs.AI | 1994-12-01 00:00:00+00:00 | For many years, the intuitions underlying partial-order planning were largely
taken for granted. Only in the past few years has there been renewed interest
in the fundamental principles underlying this paradigm. In this paper, we
present a rigorous comparative analysis of partial-order and total-order
planning by focus... | Total-Order and Partial-Order Planning: A Comparative Analysis | 1994-12-01 00:00:00+00:00 |
[arxiv.Result.Author('T. G. Dietterich'), arxiv.Result.Author('G. Bakiri')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9501101v1 | Journal of Artificial Intelligence Research, Vol 2, (1995),
263-286 | http://arxiv.org/pdf/cs/9501101v1 | cs.AI | 1995-01-01 00:00:00+00:00 | Multiclass learning problems involve finding a definition for an unknown
function f(x) whose range is a discrete set containing k > 2 values (i.e., k
``classes''). The definition is acquired by studying collections of training
examples of the form [x_i, f (x_i)]. Existing approaches to multiclass learning
problems in... | Solving Multiclass Learning Problems via Error-Correcting Output Codes | 1995-01-01 00:00:00+00:00 |
[arxiv.Result.Author('S. Hanks'), arxiv.Result.Author('D. S. Weld')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9501102v1 | Journal of Artificial Intelligence Research, Vol 2, (1995),
319-360 | http://arxiv.org/pdf/cs/9501102v1 | cs.AI | 1995-01-01 00:00:00+00:00 | The paradigms of transformational planning, case-based planning, and plan
debugging all involve a process known as plan adaptation - modifying or
repairing an old plan so it solves a new problem. In this paper we provide a
domain-independent algorithm for plan adaptation, demonstrate that it is sound,
complete, and sys... | A Domain-Independent Algorithm for Plan Adaptation | 1995-01-01 00:00:00+00:00 |
[arxiv.Result.Author('P. Cichosz')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9501103v1 | Journal of Artificial Intelligence Research, Vol 2, (1995),
287-318 | http://arxiv.org/pdf/cs/9501103v1 | cs.AI | 1995-01-01 00:00:00+00:00 | Temporal difference (TD) methods constitute a class of methods for learning
predictions in multi-step prediction problems, parameterized by a recency
factor lambda. Currently the most important application of these methods is to
temporal credit assignment in reinforcement learning. Well known reinforcement
learning alg... | Truncating Temporal Differences: On the Efficient Implementation of TD(lambda) for Reinforcement Learning | 1995-01-01 00:00:00+00:00 |
[arxiv.Result.Author('P. D. Turney')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9503102v1 | Journal of Artificial Intelligence Research, Vol 2, (1995),
369-409 | http://arxiv.org/pdf/cs/9503102v1 | cs.AI | 1995-03-01 00:00:00+00:00 | This paper introduces ICET, a new algorithm for cost-sensitive
classification. ICET uses a genetic algorithm to evolve a population of biases
for a decision tree induction algorithm. The fitness function of the genetic
algorithm is the average cost of classification when using the decision tree,
including both the cost... | Cost-Sensitive Classification: Empirical Evaluation of a Hybrid Genetic Decision Tree Induction Algorithm | 1995-03-01 00:00:00+00:00 |
[arxiv.Result.Author('S. K. Donoho'), arxiv.Result.Author('L. A. Rendell')] | ['cs.AI'] | See http://www.jair.org/ for an online appendix and other files
accompanying this article | null | http://arxiv.org/abs/cs/9504101v1 | Journal of Artificial Intelligence Research, Vol 2, (1995),
411-446 | http://arxiv.org/pdf/cs/9504101v1 | cs.AI | 1995-04-01 00:00:00+00:00 | Theory revision integrates inductive learning and background knowledge by
combining training examples with a coarse domain theory to produce a more
accurate theory. There are two challenges that theory revision and other
theory-guided systems face. First, a representation language appropriate for
the initial theory may... | Rerepresenting and Restructuring Domain Theories: A Constructive Induction Approach | 1995-04-01 00:00:00+00:00 |
[arxiv.Result.Author('P. David')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9505101v1 | Journal of Artificial Intelligence Research, Vol 2, (1995),
447-474 | http://arxiv.org/pdf/cs/9505101v1 | cs.AI | 1995-05-01 00:00:00+00:00 | Many studies have been carried out in order to increase the search efficiency
of constraint satisfaction problems; among them, some make use of structural
properties of the constraint network; others take into account semantic
properties of the constraints, generally assuming that all the constraints
possess the given ... | Using Pivot Consistency to Decompose and Solve Functional CSPs | 1995-05-01 00:00:00+00:00 |
[arxiv.Result.Author('A. Schaerf'), arxiv.Result.Author('Y. Shoham'), arxiv.Result.Author('M. Tennenholtz')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9505102v1 | Journal of Artificial Intelligence Research, Vol 2, (1995),
475-500 | http://arxiv.org/pdf/cs/9505102v1 | cs.AI | 1995-05-01 00:00:00+00:00 | We study the process of multi-agent reinforcement learning in the context of
load balancing in a distributed system, without use of either central
coordination or explicit communication. We first define a precise framework in
which to study adaptive load balancing, important features of which are its
stochastic nature ... | Adaptive Load Balancing: A Study in Multi-Agent Learning | 1995-05-01 00:00:00+00:00 |
[arxiv.Result.Author('S. J. Russell'), arxiv.Result.Author('D. Subramanian')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9505103v1 | Journal of Artificial Intelligence Research, Vol 2, (1995),
575-609 | http://arxiv.org/pdf/cs/9505103v1 | cs.AI | 1995-05-01 00:00:00+00:00 | Since its inception, artificial intelligence has relied upon a theoretical
foundation centered around perfect rationality as the desired property of
intelligent systems. We argue, as others have done, that this foundation is
inadequate because it imposes fundamentally unsatisfiable requirements. As a
result, there has ... | Provably Bounded-Optimal Agents | 1995-05-01 00:00:00+00:00 |
[arxiv.Result.Author('W. W. Cohen')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9505104v1 | Journal of Artificial Intelligence Research, Vol 2, (1995),
501-539 | http://arxiv.org/pdf/cs/9505104v1 | cs.AI | 1995-05-01 00:00:00+00:00 | We present algorithms that learn certain classes of function-free recursive
logic programs in polynomial time from equivalence queries. In particular, we
show that a single k-ary recursive constant-depth determinate clause is
learnable. Two-clause programs consisting of one learnable recursive clause and
one constant-d... | Pac-Learning Recursive Logic Programs: Efficient Algorithms | 1995-05-01 00:00:00+00:00 |
[arxiv.Result.Author('W. W. Cohen')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9505105v1 | Journal of Artificial Intelligence Research, Vol 2, (1995),
541-573 | http://arxiv.org/pdf/cs/9505105v1 | cs.AI | 1995-05-01 00:00:00+00:00 | In a companion paper it was shown that the class of constant-depth
determinate k-ary recursive clauses is efficiently learnable. In this paper we
present negative results showing that any natural generalization of this class
is hard to learn in Valiant's model of pac-learnability. In particular, we show
that the follow... | Pac-learning Recursive Logic Programs: Negative Results | 1995-05-01 00:00:00+00:00 |
[arxiv.Result.Author('M. Veloso'), arxiv.Result.Author('P. Stone')] | ['cs.AI'] | See http://www.jair.org/ for an online appendix and other files
accompanying this article | null | http://arxiv.org/abs/cs/9506101v1 | Journal of Artificial Intelligence Research, Vol 3, (1995), 25-52 | http://arxiv.org/pdf/cs/9506101v1 | cs.AI | 1995-06-01 00:00:00+00:00 | There has been evidence that least-commitment planners can efficiently handle
planning problems that involve difficult goal interactions. This evidence has
led to the common belief that delayed-commitment is the "best" possible
planning strategy. However, we recently found evidence that eager-commitment
planners can ha... | FLECS: Planning with a Flexible Commitment Strategy | 1995-06-01 00:00:00+00:00 |
[arxiv.Result.Author('R. J. Mooney'), arxiv.Result.Author('M. E. Califf')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9506102v1 | Journal of Artificial Intelligence Research, Vol 3, (1995), 1-24 | http://arxiv.org/pdf/cs/9506102v1 | cs.AI | 1995-06-01 00:00:00+00:00 | This paper presents a method for inducing logic programs from examples that
learns a new class of concepts called first-order decision lists, defined as
ordered lists of clauses each ending in a cut. The method, called FOIDL, is
based on FOIL (Quinlan, 1990) but employs intensional background knowledge and
avoids the n... | Induction of First-Order Decision Lists: Results on Learning the Past Tense of English Verbs | 1995-06-01 00:00:00+00:00 |
[arxiv.Result.Author('R. Bergmann'), arxiv.Result.Author('W. Wilke')] | ['cs.AI'] | See http://www.jair.org/ for an online appendix and other files
accompanying this article | null | http://arxiv.org/abs/cs/9507101v1 | Journal of Artificial Intelligence Research, Vol 3, (1995), 53-118 | http://arxiv.org/pdf/cs/9507101v1 | cs.AI | 1995-07-01 00:00:00+00:00 | ion is one of the most promising approaches to improve the performance of
problem solvers. In several domains abstraction by dropping sentences of a
domain description -- as used in most hierarchical planners -- has proven
useful. In this paper we present examples which illustrate significant
drawbacks of abstraction b... | Building and Refining Abstract Planning Cases by Change of Representation Language | 1995-07-01 00:00:00+00:00 |
[arxiv.Result.Author('Q. Zhao'), arxiv.Result.Author('T. Nishida')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9508101v1 | Journal of Artificial Intelligence Research, Vol 3, (1995),
119-145 | http://arxiv.org/pdf/cs/9508101v1 | cs.AI | 1995-08-01 00:00:00+00:00 | Identifying inaccurate data has long been regarded as a significant and
difficult problem in AI. In this paper, we present a new method for identifying
inaccurate data on the basis of qualitative correlations among related data.
First, we introduce the definitions of related data and qualitative
correlations among rela... | Using Qualitative Hypotheses to Identify Inaccurate Data | 1995-08-01 00:00:00+00:00 |
[arxiv.Result.Author('C. G. Giraud-Carrier'), arxiv.Result.Author('T. R. Martinez')] | ['cs.AI'] | See http://www.jair.org/ for an online appendix and other files
accompanying this article | null | http://arxiv.org/abs/cs/9508102v1 | Journal of Artificial Intelligence Research, Vol 3, (1995),
147-185 | http://arxiv.org/pdf/cs/9508102v1 | cs.AI | 1995-08-01 00:00:00+00:00 | Learning and reasoning are both aspects of what is considered to be
intelligence. Their studies within AI have been separated historically,
learning being the topic of machine learning and neural networks, and reasoning
falling under classical (or symbolic) AI. However, learning and reasoning are
in many ways interdepe... | An Integrated Framework for Learning and Reasoning | 1995-08-01 00:00:00+00:00 |
[arxiv.Result.Author('Y. Bengio'), arxiv.Result.Author('P. Frasconi')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9510101v1 | Journal of Artificial Intelligence Research, Vol 3, (1995),
249-270 | http://arxiv.org/pdf/cs/9510101v1 | cs.AI | 1995-10-01 00:00:00+00:00 | This paper studies the problem of ergodicity of transition probability
matrices in Markovian models, such as hidden Markov models (HMMs), and how it
makes very difficult the task of learning to represent long-term context for
sequential data. This phenomenon hurts the forward propagation of long-term
context informatio... | Diffusion of Context and Credit Information in Markovian Models | 1995-10-01 00:00:00+00:00 |
[arxiv.Result.Author('G. Pinkas'), arxiv.Result.Author('R. Dechter')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9510102v1 | Journal of Artificial Intelligence Research, Vol 3, (1995),
223-248 | http://arxiv.org/pdf/cs/9510102v1 | cs.AI | 1995-10-01 00:00:00+00:00 | Symmetric networks designed for energy minimization such as Boltzman machines
and Hopfield nets are frequently investigated for use in optimization,
constraint satisfaction and approximation of NP-hard problems. Nevertheless,
finding a global solution (i.e., a global minimum for the energy function) is
not guaranteed a... | Improving Connectionist Energy Minimization | 1995-10-01 00:00:00+00:00 |
[arxiv.Result.Author('K. Woods'), arxiv.Result.Author('D. Cook'), arxiv.Result.Author('L. Hall'), arxiv.Result.Author('K. Bowyer'), arxiv.Result.Author('L. Stark')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9510103v1 | Journal of Artificial Intelligence Research, Vol 3, (1995),
187-222 | http://arxiv.org/pdf/cs/9510103v1 | cs.AI | 1995-10-01 00:00:00+00:00 | Functionality-based recognition systems recognize objects at the category
level by reasoning about how well the objects support the expected function.
Such systems naturally associate a ``measure of goodness'' or ``membership
value'' with a recognized object. This measure of goodness is the result of
combining individu... | Learning Membership Functions in a Function-Based Object Recognition System | 1995-10-01 00:00:00+00:00 |
[arxiv.Result.Author('S. B. Huffman'), arxiv.Result.Author('J. E. Laird')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9511101v1 | Journal of Artificial Intelligence Research, Vol 3, (1995),
271-324 | http://arxiv.org/pdf/cs/9511101v1 | cs.AI | 1995-11-01 00:00:00+00:00 | This paper presents an approach to learning from situated, interactive
tutorial instruction within an ongoing agent. Tutorial instruction is a
flexible (and thus powerful) paradigm for teaching tasks because it allows an
instructor to communicate whatever types of knowledge an agent might need in
whatever situations mi... | Flexibly Instructable Agents | 1995-11-01 00:00:00+00:00 |
[arxiv.Result.Author('G. I. Webb')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9512101v1 | Journal of Artificial Intelligence Research, Vol 3, (1995),
431-465 | http://arxiv.org/pdf/cs/9512101v1 | cs.AI | 1995-12-01 00:00:00+00:00 | OPUS is a branch and bound search algorithm that enables efficient admissible
search through spaces for which the order of search operator application is not
significant. The algorithm's search efficiency is demonstrated with respect to
very large machine learning search spaces. The use of admissible search is of
poten... | OPUS: An Efficient Admissible Algorithm for Unordered Search | 1995-12-01 00:00:00+00:00 |
[arxiv.Result.Author('A. Broggi'), arxiv.Result.Author('S. Berte')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9512102v1 | Journal of Artificial Intelligence Research, Vol 3, (1995),
325-348 | http://arxiv.org/pdf/cs/9512102v1 | cs.AI | 1995-12-01 00:00:00+00:00 | The main aim of this work is the development of a vision-based road detection
system fast enough to cope with the difficult real-time constraints imposed by
moving vehicle applications. The hardware platform, a special-purpose massively
parallel system, has been chosen to minimize system production and operational
cost... | Vision-Based Road Detection in Automotive Systems: A Real-Time Expectation-Driven Approach | 1995-12-01 00:00:00+00:00 |
[arxiv.Result.Author('P. Idestam-Almquist')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9512103v1 | Journal of Artificial Intelligence Research, Vol 3, (1995),
467-489 | http://arxiv.org/pdf/cs/9512103v1 | cs.AI | 1995-12-01 00:00:00+00:00 | In the area of inductive learning, generalization is a main operation, and
the usual definition of induction is based on logical implication. Recently
there has been a rising interest in clausal representation of knowledge in
machine learning. Almost all inductive learning systems that perform
generalization of clauses... | Generalization of Clauses under Implication | 1995-12-01 00:00:00+00:00 |
[arxiv.Result.Author('D. Heckerman'), arxiv.Result.Author('R. Shachter')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9512104v1 | Journal of Artificial Intelligence Research, Vol 3, (1995),
405-430 | http://arxiv.org/pdf/cs/9512104v1 | cs.AI | 1995-12-01 00:00:00+00:00 | We present a definition of cause and effect in terms of decision-theoretic
primitives and thereby provide a principled foundation for causal reasoning.
Our definition departs from the traditional view of causation in that causal
assertions may vary with the set of decisions available. We argue that this
approach provid... | Decision-Theoretic Foundations for Causal Reasoning | 1995-12-01 00:00:00+00:00 |
[arxiv.Result.Author('R. Khardon')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9512105v1 | Journal of Artificial Intelligence Research, Vol 3, (1995),
349-372 | http://arxiv.org/pdf/cs/9512105v1 | cs.AI | 1995-12-01 00:00:00+00:00 | Characteristic models are an alternative, model based, representation for
Horn expressions. It has been shown that these two representations are
incomparable and each has its advantages over the other. It is therefore
natural to ask what is the cost of translating, back and forth, between these
representations. Interes... | Translating between Horn Representations and their Characteristic Models | 1995-12-01 00:00:00+00:00 |
[arxiv.Result.Author('M. Buro')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9512106v1 | Journal of Artificial Intelligence Research, Vol 3, (1995),
373-382 | http://arxiv.org/pdf/cs/9512106v1 | cs.AI | 1995-12-01 00:00:00+00:00 | This article describes an application of three well-known statistical methods
in the field of game-tree search: using a large number of classified Othello
positions, feature weights for evaluation functions with a
game-phase-independent meaning are estimated by means of logistic regression,
Fisher's linear discriminant... | Statistical Feature Combination for the Evaluation of Game Positions | 1995-12-01 00:00:00+00:00 |
[arxiv.Result.Author('S. M. Weiss'), arxiv.Result.Author('N. Indurkhya')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9512107v1 | Journal of Artificial Intelligence Research, Vol 3, (1995),
383-403 | http://arxiv.org/pdf/cs/9512107v1 | cs.AI | 1995-12-01 00:00:00+00:00 | We describe a machine learning method for predicting the value of a
real-valued function, given the values of multiple input variables. The method
induces solutions from samples in the form of ordered disjunctive normal form
(DNF) decision rules. A central objective of the method and representation is
the induction of ... | Rule-based Machine Learning Methods for Functional Prediction | 1995-12-01 00:00:00+00:00 |
[arxiv.Result.Author('P. vanBeek'), arxiv.Result.Author('D. W. Manchak')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9601101v1 | Journal of Artificial Intelligence Research, Vol 4, (1996), 1-18 | http://arxiv.org/pdf/cs/9601101v1 | cs.AI | 1996-01-01 00:00:00+00:00 | Many applications -- from planning and scheduling to problems in molecular
biology -- rely heavily on a temporal reasoning component. In this paper, we
discuss the design and empirical analysis of algorithms for a temporal
reasoning system based on Allen's influential interval-based framework for
representing temporal ... | The Design and Experimental Analysis of Algorithms for Temporal Reasoning | 1996-01-01 00:00:00+00:00 |
[arxiv.Result.Author('G. Brewka')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9602101v1 | Journal of Artificial Intelligence Research, Vol 4, (1996), 19-36 | http://arxiv.org/pdf/cs/9602101v1 | cs.AI | 1996-02-01 00:00:00+00:00 | The paper describes an extension of well-founded semantics for logic programs
with two types of negation. In this extension information about preferences
between rules can be expressed in the logical language and derived dynamically.
This is achieved by using a reserved predicate symbol and a naming technique.
Conflict... | Well-Founded Semantics for Extended Logic Programs with Dynamic Preferences | 1996-02-01 00:00:00+00:00 |
[arxiv.Result.Author('A. L. Delcher'), arxiv.Result.Author('A. J. Grove'), arxiv.Result.Author('S. Kasif'), arxiv.Result.Author('J. Pearl')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9602102v1 | Journal of Artificial Intelligence Research, Vol 4, (1996), 37-59 | http://arxiv.org/pdf/cs/9602102v1 | cs.AI | 1996-02-01 00:00:00+00:00 | Traditional databases commonly support efficient query and update procedures
that operate in time which is sublinear in the size of the database. Our goal
in this paper is to take a first step toward dynamic reasoning in probabilistic
databases with comparable efficiency. We propose a dynamic data structure that
suppor... | Logarithmic-Time Updates and Queries in Probabilistic Networks | 1996-02-01 00:00:00+00:00 |
[arxiv.Result.Author('T. Hogg')] | ['cs.AI'] | See http://www.jair.org/ for an online appendix and other files
accompanying this article | null | http://arxiv.org/abs/cs/9603101v1 | Journal of Artificial Intelligence Research, Vol 4, (1996), 91-128 | http://arxiv.org/pdf/cs/9603101v1 | cs.AI | 1996-03-01 00:00:00+00:00 | We introduce an algorithm for combinatorial search on quantum computers that
is capable of significantly concentrating amplitude into solutions for some NP
search problems, on average. This is done by exploiting the same aspects of
problem structure as used by classical backtrack methods to avoid unproductive
search ch... | Quantum Computing and Phase Transitions in Combinatorial Search | 1996-03-01 00:00:00+00:00 |
[arxiv.Result.Author('L. K. Saul'), arxiv.Result.Author('T. Jaakkola'), arxiv.Result.Author('M. I. Jordan')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9603102v1 | Journal of Artificial Intelligence Research, Vol 4, (1996), 61-76 | http://arxiv.org/pdf/cs/9603102v1 | cs.AI | 1996-03-01 00:00:00+00:00 | We develop a mean field theory for sigmoid belief networks based on ideas
from statistical mechanics. Our mean field theory provides a tractable
approximation to the true probability distribution in these networks; it also
yields a lower bound on the likelihood of evidence. We demonstrate the utility
of this framework ... | Mean Field Theory for Sigmoid Belief Networks | 1996-03-01 00:00:00+00:00 |
[arxiv.Result.Author('J. R. Quinlan')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9603103v1 | Journal of Artificial Intelligence Research, Vol 4, (1996), 77-90 | http://arxiv.org/pdf/cs/9603103v1 | cs.AI | 1996-03-01 00:00:00+00:00 | A reported weakness of C4.5 in domains with continuous attributes is
addressed by modifying the formation and evaluation of tests on continuous
attributes. An MDL-inspired penalty is applied to such tests, eliminating some
of them from consideration and altering the relative desirability of all tests.
Empirical trials ... | Improved Use of Continuous Attributes in C4.5 | 1996-03-01 00:00:00+00:00 |
[arxiv.Result.Author('D. A. Cohn'), arxiv.Result.Author('Z. Ghahramani'), arxiv.Result.Author('M. I. Jordan')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9603104v1 | Journal of Artificial Intelligence Research, Vol 4, (1996),
129-145 | http://arxiv.org/pdf/cs/9603104v1 | cs.AI | 1996-03-01 00:00:00+00:00 | For many types of machine learning algorithms, one can compute the
statistically `optimal' way to select training data. In this paper, we review
how optimal data selection techniques have been used with feedforward neural
networks. We then show how the same principles may be used to select data for
two alternative, sta... | Active Learning with Statistical Models | 1996-03-01 00:00:00+00:00 |
[arxiv.Result.Author('T. Walsh')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9604101v1 | Journal of Artificial Intelligence Research, Vol 4, (1996),
209-235 | http://arxiv.org/pdf/cs/9604101v1 | cs.AI | 1996-04-01 00:00:00+00:00 | Inductive theorem provers often diverge. This paper describes a simple
critic, a computer program which monitors the construction of inductive proofs
attempting to identify diverging proof attempts. Divergence is recognized by
means of a ``difference matching'' procedure. The critic then proposes lemmas
and generalizat... | A Divergence Critic for Inductive Proof | 1996-04-01 00:00:00+00:00 |
[arxiv.Result.Author('E. Marchiori')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9604102v1 | Journal of Artificial Intelligence Research, Vol 4, (1996),
179-208 | http://arxiv.org/pdf/cs/9604102v1 | cs.AI | 1996-04-01 00:00:00+00:00 | Termination of logic programs with negated body atoms (here called general
logic programs) is an important topic. One reason is that many computational
mechanisms used to process negated atoms, like Clark's negation as failure and
Chan's constructive negation, are based on termination conditions. This paper
introduces ... | Practical Methods for Proving Termination of General Logic Programs | 1996-04-01 00:00:00+00:00 |
[arxiv.Result.Author('D. Fisher')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9604103v1 | Journal of Artificial Intelligence Research, Vol 4, (1996),
147-178 | http://arxiv.org/pdf/cs/9604103v1 | cs.AI | 1996-04-01 00:00:00+00:00 | Clustering is often used for discovering structure in data. Clustering
systems differ in the objective function used to evaluate clustering quality
and the control strategy used to search the space of clusterings. Ideally, the
search strategy should consistently construct clusterings of high quality, but
be computation... | Iterative Optimization and Simplification of Hierarchical Clusterings | 1996-04-01 00:00:00+00:00 |
[arxiv.Result.Author('G. I. Webb')] | ['cs.AI'] | See http://www.jair.org/ for an online appendix and other files
accompanying this article | null | http://arxiv.org/abs/cs/9605101v1 | Journal of Artificial Intelligence Research, Vol 4, (1996),
397-417 | http://arxiv.org/pdf/cs/9605101v1 | cs.AI | 1996-05-01 00:00:00+00:00 | This paper presents new experimental evidence against the utility of Occam's
razor. A~systematic procedure is presented for post-processing decision trees
produced by C4.5. This procedure was derived by rejecting Occam's razor and
instead attending to the assumption that similar objects are likely to belong
to the same... | Further Experimental Evidence against the Utility of Occam's Razor | 1996-05-01 00:00:00+00:00 |
[arxiv.Result.Author('S. H. Nienhuys-Cheng'), arxiv.Result.Author('R. deWolf')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9605102v1 | Journal of Artificial Intelligence Research, Vol 4, (1996),
341-363 | http://arxiv.org/pdf/cs/9605102v1 | cs.AI | 1996-05-01 00:00:00+00:00 | The main operations in Inductive Logic Programming (ILP) are generalization
and specialization, which only make sense in a generality order. In ILP, the
three most important generality orders are subsumption, implication and
implication relative to background knowledge. The two languages used most often
are languages o... | Least Generalizations and Greatest Specializations of Sets of Clauses | 1996-05-01 00:00:00+00:00 |
[arxiv.Result.Author('L. P. Kaelbling'), arxiv.Result.Author('M. L. Littman'), arxiv.Result.Author('A. W. Moore')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9605103v1 | Journal of Artificial Intelligence Research, Vol 4, (1996),
237-285 | http://arxiv.org/pdf/cs/9605103v1 | cs.AI | 1996-05-01 00:00:00+00:00 | This paper surveys the field of reinforcement learning from a
computer-science perspective. It is written to be accessible to researchers
familiar with machine learning. Both the historical basis of the field and a
broad selection of current work are summarized. Reinforcement learning is the
problem faced by an agent t... | Reinforcement Learning: A Survey | 1996-05-01 00:00:00+00:00 |
[arxiv.Result.Author('J. Gratch'), arxiv.Result.Author('S. Chien')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9605104v1 | Journal of Artificial Intelligence Research, Vol 4, (1996),
365-396 | http://arxiv.org/pdf/cs/9605104v1 | cs.AI | 1996-05-01 00:00:00+00:00 | Although most scheduling problems are NP-hard, domain specific techniques
perform well in practice but are quite expensive to construct. In adaptive
problem-solving solving, domain specific knowledge is acquired automatically
for a general problem solver with a flexible control architecture. In this
approach, a learnin... | Adaptive Problem-solving for Large-scale Scheduling Problems: A Case Study | 1996-05-01 00:00:00+00:00 |
[arxiv.Result.Author('P. Tadepalli'), arxiv.Result.Author('B. K. Natarajan')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9605105v1 | Journal of Artificial Intelligence Research, Vol 4, (1996),
445-475 | http://arxiv.org/pdf/cs/9605105v1 | cs.AI | 1996-05-01 00:00:00+00:00 | Speedup learning seeks to improve the computational efficiency of problem
solving with experience. In this paper, we develop a formal framework for
learning efficient problem solving from random problems and their solutions. We
apply this framework to two different representations of learned knowledge,
namely control r... | A Formal Framework for Speedup Learning from Problems and Solutions | 1996-05-01 00:00:00+00:00 |
[arxiv.Result.Author('L. Pryor'), arxiv.Result.Author('G. Collins')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9605106v1 | Journal of Artificial Intelligence Research, Vol 4, (1996),
287-339 | http://arxiv.org/pdf/cs/9605106v1 | cs.AI | 1996-05-01 00:00:00+00:00 | A fundamental assumption made by classical AI planners is that there is no
uncertainty in the world: the planner has full knowledge of the conditions
under which the plan will be executed and the outcome of every action is fully
predictable. These planners cannot therefore construct contingency plans, i.e.,
plans in wh... | 2Planning for Contingencies: A Decision-based Approach | 1996-05-01 00:00:00+00:00 |
[arxiv.Result.Author('S. Bhansali'), arxiv.Result.Author('G. A. Kramer'), arxiv.Result.Author('T. J. Hoar')] | ['cs.AI'] | See http://www.jair.org/ for an online appendix and other files
accompanying this article | null | http://arxiv.org/abs/cs/9606101v1 | Journal of Artificial Intelligence Research, Vol 4, (1996),
419-443 | http://arxiv.org/pdf/cs/9606101v1 | cs.AI | 1996-06-01 00:00:00+00:00 | An important problem in geometric reasoning is to find the configuration of a
collection of geometric bodies so as to satisfy a set of given constraints.
Recently, it has been suggested that this problem can be solved efficiently by
symbolically reasoning about geometry. This approach, called degrees of freedom
analysi... | A Principled Approach Towards Symbolic Geometric Constraint Satisfaction | 1996-06-01 00:00:00+00:00 |
[arxiv.Result.Author('R. I. Brafman'), arxiv.Result.Author('M. Tennenholtz')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9606102v1 | Journal of Artificial Intelligence Research, Vol 4, (1996),
477-507 | http://arxiv.org/pdf/cs/9606102v1 | cs.AI | 1996-06-01 00:00:00+00:00 | Motivated by the control theoretic distinction between controllable and
uncontrollable events, we distinguish between two types of agents within a
multi-agent system: controllable agents, which are directly controlled by the
system's designer, and uncontrollable agents, which are not under the
designer's direct control... | On Partially Controlled Multi-Agent Systems | 1996-06-01 00:00:00+00:00 |
[arxiv.Result.Author('K. Yip'), arxiv.Result.Author('F. Zhao')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9608103v1 | Journal of Artificial Intelligence Research, Vol 5, (1996), 1-26 | http://arxiv.org/pdf/cs/9608103v1 | cs.AI | 1996-08-01 00:00:00+00:00 | Visual thinking plays an important role in scientific reasoning. Based on the
research in automating diverse reasoning tasks about dynamical systems,
nonlinear controllers, kinematic mechanisms, and fluid motion, we have
identified a style of visual thinking, imagistic reasoning. Imagistic reasoning
organizes computati... | Spatial Aggregation: Theory and Applications | 1996-08-01 00:00:00+00:00 |
[arxiv.Result.Author('R. Ben-Eliyahu')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9608104v1 | Journal of Artificial Intelligence Research, Vol 5, (1996), 27-52 | http://arxiv.org/pdf/cs/9608104v1 | cs.AI | 1996-08-01 00:00:00+00:00 | Finding the stable models of a knowledge base is a significant computational
problem in artificial intelligence. This task is at the computational heart of
truth maintenance systems, autoepistemic logic, and default logic.
Unfortunately, it is NP-hard. In this paper we present a hierarchy of classes
of knowledge bases,... | A Hierarchy of Tractable Subsets for Computing Stable Models | 1996-08-01 00:00:00+00:00 |
[arxiv.Result.Author('A. Gerevini'), arxiv.Result.Author('L. Schubert')] | ['cs.AI'] | See http://www.jair.org/ for an online appendix and other files
accompanying this article | null | http://arxiv.org/abs/cs/9609101v1 | Journal of Artificial Intelligence Research, Vol 5, (1996), 95-137 | http://arxiv.org/pdf/cs/9609101v1 | cs.AI | 1996-09-01 00:00:00+00:00 | We propose some domain-independent techniques for bringing well-founded
partial-order planners closer to practicality. The first two techniques are
aimed at improving search control while keeping overhead costs low. One is
based on a simple adjustment to the default A* heuristic used by UCPOP to
select plans for refine... | Accelerating Partial-Order Planners: Some Techniques for Effective Search Control and Pruning | 1996-09-01 00:00:00+00:00 |
[arxiv.Result.Author('D. J. Litman')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9609102v1 | Journal of Artificial Intelligence Research, Vol 5, (1996), 53-94 | http://arxiv.org/pdf/cs/9609102v1 | cs.AI | 1996-09-01 00:00:00+00:00 | Cue phrases may be used in a discourse sense to explicitly signal discourse
structure, but also in a sentential sense to convey semantic rather than
structural information. Correctly classifying cue phrases as discourse or
sentential is critical in natural language processing systems that exploit
discourse structure, e... | Cue Phrase Classification Using Machine Learning | 1996-09-01 00:00:00+00:00 |
[arxiv.Result.Author('G. Zlotkin'), arxiv.Result.Author('J. S. Rosenschein')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9610101v1 | Journal of Artificial Intelligence Research, Vol 5, (1996),
163-238 | http://arxiv.org/pdf/cs/9610101v1 | cs.AI | 1996-10-01 00:00:00+00:00 | This paper lays part of the groundwork for a domain theory of negotiation,
that is, a way of classifying interactions so that it is clear, given a domain,
which negotiation mechanisms and strategies are appropriate. We define State
Oriented Domains, a general category of interaction. Necessary and sufficient
conditions... | Mechanisms for Automated Negotiation in State Oriented Domains | 1996-10-01 00:00:00+00:00 |
[arxiv.Result.Author('J. R. Quinlan')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9610102v1 | Journal of Artificial Intelligence Research, Vol 5, (1996),
139-161 | http://arxiv.org/pdf/cs/9610102v1 | cs.AI | 1996-10-01 00:00:00+00:00 | First-order learning involves finding a clause-form definition of a relation
from examples of the relation and relevant background information. In this
paper, a particular first-order learning system is modified to customize it for
finding definitions of functional relations. This restriction leads to faster
learning t... | Learning First-Order Definitions of Functions | 1996-10-01 00:00:00+00:00 |
[arxiv.Result.Author('R. A Helzerman'), arxiv.Result.Author('M. P. Harper')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9611101v1 | Journal of Artificial Intelligence Research, Vol 5, (1996),
239-288 | http://arxiv.org/pdf/cs/9611101v1 | cs.AI | 1996-11-01 00:00:00+00:00 | This paper describes an extension to the constraint satisfaction problem
(CSP) called MUSE CSP (MUltiply SEgmented Constraint Satisfaction Problem).
This extension is especially useful for those problems which segment into
multiple sets of partially shared variables. Such problems arise naturally in
signal processing a... | MUSE CSP: An Extension to the Constraint Satisfaction Problem | 1996-11-01 00:00:00+00:00 |
[arxiv.Result.Author('N. L. Zhang'), arxiv.Result.Author('D. Poole')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9612101v1 | Journal of Artificial Intelligence Research, Vol 5, (1996),
301-328 | http://arxiv.org/pdf/cs/9612101v1 | cs.AI | 1996-12-01 00:00:00+00:00 | A new method is proposed for exploiting causal independencies in exact
Bayesian network inference. A Bayesian network can be viewed as representing a
factorization of a joint probability into the multiplication of a set of
conditional probabilities. We present a notion of causal independence that
enables one to further... | Exploiting Causal Independence in Bayesian Network Inference | 1996-12-01 00:00:00+00:00 |
[arxiv.Result.Author('J. C. Schlimmer'), arxiv.Result.Author('P. C. Wells')] | ['cs.AI'] | See http://www.jair.org/ for an online appendix and other files
accompanying this article | null | http://arxiv.org/abs/cs/9612102v1 | Journal of Artificial Intelligence Research, Vol 5, (1996),
329-349 | http://arxiv.org/pdf/cs/9612102v1 | cs.AI | 1996-12-01 00:00:00+00:00 | Efficiently entering information into a computer is key to enjoying the
benefits of computing. This paper describes three intelligent user interfaces:
handwriting recognition, adaptive menus, and predictive fillin. In the context
of adding a personUs name and address to an electronic organizer, tests show
handwriting r... | Quantitative Results Comparing Three Intelligent Interfaces for Information Capture: A Case Study Adding Name Information into an Electronic Personal Organizer | 1996-12-01 00:00:00+00:00 |
[arxiv.Result.Author('L. M. deCampos')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9612103v1 | Journal of Artificial Intelligence Research, Vol 5, (1996),
289-300 | http://arxiv.org/pdf/cs/9612103v1 | cs.AI | 1996-12-01 00:00:00+00:00 | Decomposable dependency models possess a number of interesting and useful
properties. This paper presents new characterizations of decomposable models in
terms of independence relationships, which are obtained by adding a single
axiom to the well-known set characterizing dependency models that are
isomorphic to undirec... | Characterizations of Decomposable Dependency Models | 1996-12-01 00:00:00+00:00 |
[arxiv.Result.Author('D. R. Wilson'), arxiv.Result.Author('T. R. Martinez')] | ['cs.AI'] | See http://www.jair.org/ for an online appendix and other files
accompanying this article | null | http://arxiv.org/abs/cs/9701101v1 | Journal of Artificial Intelligence Research, Vol 6, (1997), 1-34 | http://arxiv.org/pdf/cs/9701101v1 | cs.AI | 1997-01-01 00:00:00+00:00 | Instance-based learning techniques typically handle continuous and linear
input values well, but often do not handle nominal input attributes
appropriately. The Value Difference Metric (VDM) was designed to find
reasonable distance values between nominal attribute values, but it largely
ignores continuous attributes, r... | Improved Heterogeneous Distance Functions | 1997-01-01 00:00:00+00:00 |
[arxiv.Result.Author('S. Wermter'), arxiv.Result.Author('V. Weber')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9701102v1 | Journal of Artificial Intelligence Research, Vol 6, (1997), 35-85 | http://arxiv.org/pdf/cs/9701102v1 | cs.AI | 1997-01-01 00:00:00+00:00 | Previous approaches of analyzing spontaneously spoken language often have
been based on encoding syntactic and semantic knowledge manually and
symbolically. While there has been some progress using statistical or
connectionist language models, many current spoken- language systems still use
a relatively brittle, hand-c... | SCREEN: Learning a Flat Syntactic and Semantic Spoken Language Analysis Using Artificial Neural Networks | 1997-01-01 00:00:00+00:00 |
[arxiv.Result.Author('G. DeGiacomo'), arxiv.Result.Author('M. Lenzerini')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9703101v1 | Journal of Artificial Intelligence Research, Vol 6, (1997), 87-110 | http://arxiv.org/pdf/cs/9703101v1 | cs.AI | 1997-03-01 00:00:00+00:00 | Most modern formalisms used in Databases and Artificial Intelligence for
describing an application domain are based on the notions of class (or concept)
and relationship among classes. One interesting feature of such formalisms is
the possibility of defining a class, i.e., providing a set of properties that
precisely c... | A Uniform Framework for Concept Definitions in Description Logics | 1997-03-01 00:00:00+00:00 |
[arxiv.Result.Author('P. Agre'), arxiv.Result.Author('I. Horswill')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9704101v1 | Journal of Artificial Intelligence Research, Vol 6, (1997),
111-145 | http://arxiv.org/pdf/cs/9704101v1 | cs.AI | 1997-04-01 00:00:00+00:00 | We argue that the analysis of agent/environment interactions should be
extended to include the conventions and invariants maintained by agents
throughout their activity. We refer to this thicker notion of environment as a
lifeworld and present a partial set of formal tools for describing structures
of lifeworlds and th... | Lifeworld Analysis | 1997-04-01 00:00:00+00:00 |
[arxiv.Result.Author('A. Darwiche'), arxiv.Result.Author('G. Provan')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9705101v1 | Journal of Artificial Intelligence Research, Vol 6, (1997),
147-176 | http://arxiv.org/pdf/cs/9705101v1 | cs.AI | 1997-05-01 00:00:00+00:00 | We describe a new paradigm for implementing inference in belief networks,
which consists of two steps: (1) compiling a belief network into an arithmetic
expression called a Query DAG (Q-DAG); and (2) answering queries using a simple
evaluation algorithm. Each node of a Q-DAG represents a numeric operation, a
number, or... | Query DAGs: A Practical Paradigm for Implementing Belief-Network Inference | 1997-05-01 00:00:00+00:00 |
[arxiv.Result.Author('D. W. Opitz'), arxiv.Result.Author('J. W. Shavlik')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9705102v1 | Journal of Artificial Intelligence Research, Vol 6, (1997),
177-209 | http://arxiv.org/pdf/cs/9705102v1 | cs.AI | 1997-05-01 00:00:00+00:00 | An algorithm that learns from a set of examples should ideally be able to
exploit the available resources of (a) abundant computing power and (b)
domain-specific knowledge to improve its ability to generalize. Connectionist
theory-refinement systems, which use background knowledge to select a neural
network's topology ... | Connectionist Theory Refinement: Genetically Searching the Space of Network Topologies | 1997-05-01 00:00:00+00:00 |
[arxiv.Result.Author('M. E. Pollack'), arxiv.Result.Author('D. Joslin'), arxiv.Result.Author('M. Paolucci')] | ['cs.AI'] | See http://www.jair.org/ for an online appendix and other files
accompanying this article | null | http://arxiv.org/abs/cs/9706101v1 | Journal of Artificial Intelligence Research, Vol 6, (1997),
223-262 | http://arxiv.org/pdf/cs/9706101v1 | cs.AI | 1997-06-01 00:00:00+00:00 | Several recent studies have compared the relative efficiency of alternative
flaw selection strategies for partial-order causal link (POCL) planning. We
review this literature, and present new experimental results that generalize
the earlier work and explain some of the discrepancies in it. In particular, we
describe th... | Flaw Selection Strategies for Partial-Order Planning | 1997-06-01 00:00:00+00:00 |
[arxiv.Result.Author('P. Jonsson'), arxiv.Result.Author('T. Drakengren')] | ['cs.AI'] | See http://www.jair.org/ for an online appendix and other files
accompanying this article | null | http://arxiv.org/abs/cs/9706102v1 | Journal of Artificial Intelligence Research, Vol 6, (1997),
211-221 | http://arxiv.org/pdf/cs/9706102v1 | cs.AI | 1997-06-01 00:00:00+00:00 | We investigate the computational properties of the spatial algebra RCC-5
which is a restricted version of the RCC framework for spatial reasoning. The
satisfiability problem for RCC-5 is known to be NP-complete but not much is
known about its approximately four billion subclasses. We provide a complete
classification o... | A Complete Classification of Tractability in RCC-5 | 1997-06-01 00:00:00+00:00 |
[arxiv.Result.Author('D. L. Mammen'), arxiv.Result.Author('T. Hogg')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9707101v1 | Journal of Artificial Intelligence Research, Vol 7, (1997), 47-66 | http://arxiv.org/pdf/cs/9707101v1 | cs.AI | 1997-07-01 00:00:00+00:00 | The easy-hard-easy pattern in the difficulty of combinatorial search problems
as constraints are added has been explained as due to a competition between the
decrease in number of solutions and increased pruning. We test the generality
of this explanation by examining one of its predictions: if the number of
solutions ... | A New Look at the Easy-Hard-Easy Pattern of Combinatorial Search Difficulty | 1997-07-01 00:00:00+00:00 |
[arxiv.Result.Author('T. Drakengren'), arxiv.Result.Author('P. Jonsson')] | ['cs.AI'] | See http://www.jair.org/ for an online appendix and other files
accompanying this article | null | http://arxiv.org/abs/cs/9707102v1 | Journal of Artificial Intelligence Research, Vol 7, (1997), 25-45 | http://arxiv.org/pdf/cs/9707102v1 | cs.AI | 1997-07-01 00:00:00+00:00 | This paper combines two important directions of research in temporal
resoning: that of finding maximal tractable subclasses of Allen's interval
algebra, and that of reasoning with metric temporal information. Eight new
maximal tractable subclasses of Allen's interval algebra are presented, some of
them subsuming previo... | Eight Maximal Tractable Subclasses of Allen's Algebra with Metric Time | 1997-07-01 00:00:00+00:00 |
[arxiv.Result.Author('J. Y. Halpern')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9707103v1 | Journal of Artificial Intelligence Research, Vol 7, (1997), 1-24 | http://arxiv.org/pdf/cs/9707103v1 | cs.AI | 1997-07-01 00:00:00+00:00 | Starting with a likelihood or preference order on worlds, we extend it to a
likelihood ordering on sets of worlds in a natural way, and examine the
resulting logic. Lewis earlier considered such a notion of relative likelihood
in the context of studying counterfactuals, but he assumed a total preference
order on worlds... | Defining Relative Likelihood in Partially-Ordered Preferential Structures | 1997-07-01 00:00:00+00:00 |
[arxiv.Result.Author('M. Tambe')] | ['cs.AI'] | See http://www.jair.org/ for an online appendix and other files
accompanying this article | null | http://arxiv.org/abs/cs/9709101v1 | Journal of Artificial Intelligence Research, Vol 7, (1997), 83-124 | http://arxiv.org/pdf/cs/9709101v1 | cs.AI | 1997-09-01 00:00:00+00:00 | Many AI researchers are today striving to build agent teams for complex,
dynamic multi-agent domains, with intended applications in arenas such as
education, training, entertainment, information integration, and collective
robotics. Unfortunately, uncertainties in these complex, dynamic domains
obstruct coherent teamwo... | Towards Flexible Teamwork | 1997-09-01 00:00:00+00:00 |
[arxiv.Result.Author('C. G. Nevill-Manning'), arxiv.Result.Author('I. H. Witten')] | ['cs.AI'] | See http://www.jair.org/ for an online appendix and other files
accompanying this article | null | http://arxiv.org/abs/cs/9709102v1 | Journal of Artificial Intelligence Research, Vol 7, (1997), 67-82 | http://arxiv.org/pdf/cs/9709102v1 | cs.AI | 1997-09-01 00:00:00+00:00 | SEQUITUR is an algorithm that infers a hierarchical structure from a sequence
of discrete symbols by replacing repeated phrases with a grammatical rule that
generates the phrase, and continuing this process recursively. The result is a
hierarchical representation of the original sequence, which offers insights
into its... | Identifying Hierarchical Structure in Sequences: A linear-time algorithm | 1997-09-01 00:00:00+00:00 |
[arxiv.Result.Author('L. H. Ihrig'), arxiv.Result.Author('S. Kambhampati')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9711102v1 | Journal of Artificial Intelligence Research, Vol 7, (1997),
161-198 | http://arxiv.org/pdf/cs/9711102v1 | cs.AI | 1997-11-01 00:00:00+00:00 | Case-Based Planning (CBP) provides a way of scaling up domain-independent
planning to solve large problems in complex domains. It replaces the detailed
and lengthy search for a solution with the retrieval and adaptation of previous
planning experiences. In general, CBP has been demonstrated to improve
performance over ... | Storing and Indexing Plan Derivations through Explanation-based Analysis of Retrieval Failures | 1997-11-01 00:00:00+00:00 |
[arxiv.Result.Author('N. L. Zhang'), arxiv.Result.Author('W. Liu')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9711103v1 | Journal of Artificial Intelligence Research, Vol 7, (1997),
199-230 | http://arxiv.org/pdf/cs/9711103v1 | cs.AI | 1997-11-01 00:00:00+00:00 | Partially observable Markov decision processes (POMDPs) are a natural model
for planning problems where effects of actions are nondeterministic and the
state of the world is not completely observable. It is difficult to solve
POMDPs exactly. This paper proposes a new approximation scheme. The basic idea
is to transform... | A Model Approximation Scheme for Planning in Partially Observable Stochastic Domains | 1997-11-01 00:00:00+00:00 |
[arxiv.Result.Author('D. Monderer'), arxiv.Result.Author('M. Tennenholtz')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9711104v1 | Journal of Artificial Intelligence Research, Vol 7, (1997),
231-248 | http://arxiv.org/pdf/cs/9711104v1 | cs.AI | 1997-11-01 00:00:00+00:00 | The model of a non-Bayesian agent who faces a repeated game with incomplete
information against Nature is an appropriate tool for modeling general
agent-environment interactions. In such a model the environment state
(controlled by Nature) may change arbitrarily, and the feedback/reward function
is initially unknown. T... | Dynamic Non-Bayesian Decision Making | 1997-11-01 00:00:00+00:00 |
[arxiv.Result.Author('J. Frank'), arxiv.Result.Author('P. Cheeseman'), arxiv.Result.Author('J. Stutz')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9712101v1 | Journal of Artificial Intelligence Research, Vol 7, (1997),
249-281 | http://arxiv.org/pdf/cs/9712101v1 | cs.AI | 1997-12-01 00:00:00+00:00 | Local search algorithms for combinatorial search problems frequently
encounter a sequence of states in which it is impossible to improve the value
of the objective function; moves through these regions, called plateau moves,
dominate the time spent in local search. We analyze and characterize plateaus
for three differe... | When Gravity Fails: Local Search Topology | 1997-12-01 00:00:00+00:00 |
[arxiv.Result.Author('H. Kaindl'), arxiv.Result.Author('G. Kainz')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9712102v1 | Journal of Artificial Intelligence Research, Vol 7, (1997),
283-317 | http://arxiv.org/pdf/cs/9712102v1 | cs.AI | 1997-12-01 00:00:00+00:00 | The assessment of bidirectional heuristic search has been incorrect since it
was first published more than a quarter of a century ago. For quite a long
time, this search strategy did not achieve the expected results, and there was
a major misunderstanding about the reasons behind it. Although there is still
wide-spread... | Bidirectional Heuristic Search Reconsidered | 1997-12-01 00:00:00+00:00 |
[arxiv.Result.Author('G. Gogic'), arxiv.Result.Author('C. H. Papadimitriou'), arxiv.Result.Author('M. Sideri')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9801101v1 | Journal of Artificial Intelligence Research, Vol 8, (1998), 23-37 | http://arxiv.org/pdf/cs/9801101v1 | cs.AI | 1998-01-01 00:00:00+00:00 | Approximating a general formula from above and below by Horn formulas (its
Horn envelope and Horn core, respectively) was proposed by Selman and Kautz
(1991, 1996) as a form of ``knowledge compilation,'' supporting rapid
approximate reasoning; on the negative side, this scheme is static in that it
supports no updates, ... | Incremental Recompilation of Knowledge | 1998-01-01 00:00:00+00:00 |
[arxiv.Result.Author('J. Engelfriet')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9801102v1 | Journal of Artificial Intelligence Research, Vol 8, (1998), 1-21 | http://arxiv.org/pdf/cs/9801102v1 | cs.AI | 1998-01-01 00:00:00+00:00 | An important characteristic of many logics for Artificial Intelligence is
their nonmonotonicity. This means that adding a formula to the premises can
invalidate some of the consequences. There may, however, exist formulae that
can always be safely added to the premises without destroying any of the
consequences: we say... | Monotonicity and Persistence in Preferential Logics | 1998-01-01 00:00:00+00:00 |
[arxiv.Result.Author('B. Srivastava'), arxiv.Result.Author('S. Kambhampati')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9803101v1 | Journal of Artificial Intelligence Research, Vol 8, (1998), 93-128 | http://arxiv.org/pdf/cs/9803101v1 | cs.AI | 1998-03-01 00:00:00+00:00 | Existing plan synthesis approaches in artificial intelligence fall into two
categories -- domain independent and domain dependent. The domain independent
approaches are applicable across a variety of domains, but may not be very
efficient in any one given domain. The domain dependent approaches need to be
(re)designed ... | Synthesizing Customized Planners from Specifications | 1998-03-01 00:00:00+00:00 |
[arxiv.Result.Author('A. Moore'), arxiv.Result.Author('M. S. Lee')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9803102v1 | Journal of Artificial Intelligence Research, Vol 8, (1998), 67-91 | http://arxiv.org/pdf/cs/9803102v1 | cs.AI | 1998-03-01 00:00:00+00:00 | This paper introduces new algorithms and data structures for quick counting
for machine learning datasets. We focus on the counting task of constructing
contingency tables, but our approach is also applicable to counting the number
of records in a dataset that match conjunctive queries. Subject to certain
assumptions, ... | Cached Sufficient Statistics for Efficient Machine Learning with Large Datasets | 1998-03-01 00:00:00+00:00 |
[arxiv.Result.Author('S. Argamon-Engelson'), arxiv.Result.Author('M. Koppel')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9803103v1 | Journal of Artificial Intelligence Research, Vol 8, (1998), 39-65 | http://arxiv.org/pdf/cs/9803103v1 | cs.AI | 1998-03-01 00:00:00+00:00 | In this paper we consider the problem of `theory patching', in which we are
given a domain theory, some of whose components are indicated to be possibly
flawed, and a set of labeled training examples for the domain concept. The
theory patching problem is to revise only the indicated components of the
theory, such that ... | Tractability of Theory Patching | 1998-03-01 00:00:00+00:00 |
[arxiv.Result.Author('J. Fürnkranz')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | 10.1613/jair.487 | http://arxiv.org/abs/cs/9805101v1 | Journal of Artificial Intelligence Research, Vol 8, (1998),
129-164 | http://arxiv.org/pdf/cs/9805101v1 | cs.AI | 1998-05-01 00:00:00+00:00 | In this paper we re-investigate windowing for rule learning algorithms. We
show that, contrary to previous results for decision tree learning, windowing
can in fact achieve significant run-time gains in noise-free domains and
explain the different behavior of rule learning algorithms by the fact that
they learn each ru... | Integrative Windowing | 1998-05-01 00:00:00+00:00 |
[arxiv.Result.Author('A. Darwiche')] | ['cs.AI'] | See http://www.jair.org/ for any accompanying files | null | http://arxiv.org/abs/cs/9806101v1 | Journal of Artificial Intelligence Research, Vol 8, (1998),
165-222 | http://arxiv.org/pdf/cs/9806101v1 | cs.AI | 1998-06-01 00:00:00+00:00 | This paper presents a comprehensive approach for model-based diagnosis which
includes proposals for characterizing and computing preferred diagnoses,
assuming that the system description is augmented with a system structure (a
directed graph explicating the interconnections between system components).
Specifically, we ... | Model-Based Diagnosis using Structured System Descriptions | 1998-06-01 00:00:00+00:00 |
[arxiv.Result.Author('L. Finkelstein'), arxiv.Result.Author('S. Markovitch')] | ['cs.AI'] | See http://www.jair.org/ for an online appendix and other files
accompanying this article | null | http://arxiv.org/abs/cs/9806102v1 | Journal of Artificial Intelligence Research, Vol 8, (1998),
223-263 | http://arxiv.org/pdf/cs/9806102v1 | cs.AI | 1998-06-01 00:00:00+00:00 | One of the most common mechanisms used for speeding up problem solvers is
macro-learning. Macros are sequences of basic operators acquired during problem
solving. Macros are used by the problem solver as if they were basic operators.
The major problem that macro-learning presents is the vast number of macros
that are a... | A Selective Macro-learning Algorithm and its Application to the NxN Sliding-Tile Puzzle | 1998-06-01 00:00:00+00:00 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.