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20,202 | FMAP: Distributed Cooperative Multi-Agent Planning | cs.AI | This paper proposes FMAP (Forward Multi-Agent Planning), a fully-distributed
multi-agent planning method that integrates planning and coordination. Although
FMAP is specifically aimed at solving problems that require cooperation among
agents, the flexibility of the domain-independent planning model allows FMAP to
tackl... | computer science |
20,203 | An approach to multi-agent planning with incomplete information | cs.AI | Multi-agent planning (MAP) approaches have been typically conceived for
independent or loosely-coupled problems to enhance the benefits of distributed
planning between autonomous agents as solving this type of problems require
less coordination between the agents' sub-plans. However, when it comes to
tightly-coupled ag... | computer science |
20,204 | A Flexible Coupling Approach to Multi-Agent Planning under Incomplete
Information | cs.AI | Multi-agent planning (MAP) approaches are typically oriented at solving
loosely-coupled problems, being ineffective to deal with more complex,
strongly-related problems. In most cases, agents work under complete
information, building complete knowledge bases. The present article introduces
a general-purpose MAP framewo... | computer science |
20,205 | Knowledge reduction of dynamic covering decision information systems
with immigration of more objects | cs.AI | In practical situations, it is of interest to investigate computing
approximations of sets as an important step of knowledge reduction of dynamic
covering decision information systems. In this paper, we present incremental
approaches to computing the type-1 and type-2 characteristic matrices of
dynamic coverings whose ... | computer science |
20,206 | Managing Multi-Granular Linguistic Distribution Assessments in
Large-Scale Multi-Attribute Group Decision Making | cs.AI | Linguistic large-scale group decision making (LGDM) problems are more and
more common nowadays. In such problems a large group of decision makers are
involved in the decision process and elicit linguistic information that are
usually assessed in different linguistic scales with diverse granularity
because of decision m... | computer science |
20,207 | Dual Decomposition from the Perspective of Relax, Compensate and then
Recover | cs.AI | Relax, Compensate and then Recover (RCR) is a paradigm for approximate
inference in probabilistic graphical models that has previously provided
theoretical and practical insights on iterative belief propagation and some of
its generalizations. In this paper, we characterize the technique of dual
decomposition in the te... | computer science |
20,208 | The Neutrosophic Entropy and its Five Components | cs.AI | This paper presents two variants of penta-valued representation for
neutrosophic entropy. The first is an extension of Kaufmann's formula and the
second is an extension of Kosko's formula.
Based on the primary three-valued information represented by the degree of
truth, degree of falsity and degree of neutrality ther... | computer science |
20,209 | An Optimized Hybrid Approach for Path Finding | cs.AI | Path finding algorithm addresses problem of finding shortest path from source
to destination avoiding obstacles. There exist various search algorithms namely
A*, Dijkstra's and ant colony optimization. Unlike most path finding algorithms
which require destination co-ordinates to compute path, the proposed algorithm
com... | computer science |
20,210 | Quantitative Analysis of Whether Machine Intelligence Can Surpass Human
Intelligence | cs.AI | Whether the machine intelligence can surpass the human intelligence is a
controversial issue. On the basis of traditional IQ, this article presents the
Universal IQ test method suitable for both the machine intelligence and the
human intelligence. With the method, machine and human intelligences were
divided into 4 maj... | computer science |
20,211 | Ultimate Intelligence Part II: Physical Measure and Complexity of
Intelligence | cs.AI | We continue our analysis of volume and energy measures that are appropriate
for quantifying inductive inference systems. We extend logical depth and
conceptual jump size measures in AIT to stochastic problems, and physical
measures that involve volume and energy. We introduce a graphical model of
computational complexi... | computer science |
20,212 | Harnessing Natural Fluctuations: Analogue Computer for Efficient
Socially Maximal Decision Making | cs.AI | Each individual handles many tasks of finding the most profitable option from
a set of options that stochastically provide rewards. Our society comprises a
collection of such individuals, and the society is expected to maximise the
total rewards, while the individuals compete for common rewards. Such
collective decisio... | computer science |
20,213 | Fuzzy approaches to context variable in fuzzy geographically weighted
clustering | cs.AI | Fuzzy Geographically Weighted Clustering (FGWC) is considered as a suitable
tool for the analysis of geo-demographic data that assists the provision and
planning of products and services to local people. Context variables were
attached to FGWC in order to accelerate the computing speed of the algorithm
and to focus the... | computer science |
20,214 | Towards Verifiably Ethical Robot Behaviour | cs.AI | Ensuring that autonomous systems work ethically is both complex and
difficult. However, the idea of having an additional `governor' that assesses
options the system has, and prunes them to select the most ethical choices is
well understood. Recent work has produced such a governor consisting of a
`consequence engine' t... | computer science |
20,215 | How do you revise your belief set with %$;@*? | cs.AI | In the classic AGM belief revision theory, beliefs are static and do not
change their own shape. For instance, if p is accepted by a rational agent, it
will remain p to the agent. But such rarely happens to us. Often, when we
accept some information p, what is actually accepted is not the whole p, but
only a portion of... | computer science |
20,216 | Reasoning about Unmodelled Concepts - Incorporating Class Taxonomies in
Probabilistic Relational Models | cs.AI | A key problem in the application of first-order probabilistic methods is the
enormous size of graphical models they imply. The size results from the
possible worlds that can be generated by a domain of objects and relations. One
of the reasons for this explosion is that so far the approaches do not
sufficiently exploit... | computer science |
20,217 | Ascribing Consciousness to Artificial Intelligence | cs.AI | This paper critically assesses the anti-functionalist stance on consciousness
adopted by certain advocates of integrated information theory (IIT), a
corollary of which is that human-level artificial intelligence implemented on
conventional computing hardware is necessarily not conscious. The critique
draws on variation... | computer science |
20,218 | Generalized Support and Formal Development of Constraint Propagators | cs.AI | Constraint programming is a family of techniques for solving combinatorial
problems, where the problem is modelled as a set of decision variables
(typically with finite domains) and a set of constraints that express relations
among the decision variables. One key concept in constraint programming is
propagation: reason... | computer science |
20,219 | Logical Conditional Preference Theories | cs.AI | CP-nets represent the dominant existing framework for expressing qualitative
conditional preferences between alternatives, and are used in a variety of
areas including constraint solving. Over the last fifteen years, a significant
literature has developed exploring semantics, algorithms, implementation and
use of CP-ne... | computer science |
20,220 | Information Gathering in Networks via Active Exploration | cs.AI | How should we gather information in a network, where each node's visibility
is limited to its local neighborhood? This problem arises in numerous
real-world applications, such as surveying and task routing in social networks,
team formation in collaborative networks and experimental design with
dependency constraints. ... | computer science |
20,221 | Controlled Query Evaluation for Datalog and OWL 2 Profile Ontologies | cs.AI | We study confidentiality enforcement in ontologies under the Controlled Query
Evaluation framework, where a policy specifies the sensitive information and a
censor ensures that query answers that may compromise the policy are not
returned. We focus on censors that ensure confidentiality while maximising
information acc... | computer science |
20,222 | Preferential Multi-Context Systems | cs.AI | Multi-context systems (MCS) presented by Brewka and Eiter can be considered
as a promising way to interlink decentralized and heterogeneous knowledge
contexts. In this paper, we propose preferential multi-context systems (PMCS),
which provide a framework for incorporating a total preorder relation over
contexts in a mu... | computer science |
20,223 | Theory of Semi-Instantiation in Abstract Argumentation | cs.AI | We study instantiated abstract argumentation frames of the form $(S,R,I)$,
where $(S,R)$ is an abstract argumentation frame and where the arguments $x$ of
$S$ are instantiated by $I(x)$ as well formed formulas of a well known logic,
for example as Boolean formulas or as predicate logic formulas or as modal
logic formul... | computer science |
20,224 | Further Connections Between Contract-Scheduling and Ray-Searching
Problems | cs.AI | This paper addresses two classes of different, yet interrelated optimization
problems. The first class of problems involves a robot that must locate a
hidden target in an environment that consists of a set of concurrent rays. The
second class pertains to the design of interruptible algorithms by means of a
schedule of ... | computer science |
20,225 | A Probabilistic Framework for Representing Dialog Systems and
Entropy-Based Dialog Management through Dynamic Stochastic State Evolution | cs.AI | In this paper, we present a probabilistic framework for goal-driven spoken
dialog systems. A new dynamic stochastic state (DS-state) is then defined to
characterize the goal set of a dialog state at different stages of the dialog
process. Furthermore, an entropy minimization dialog management(EMDM) strategy
is also pro... | computer science |
20,226 | Building Hierarchies of Concepts via Crowdsourcing | cs.AI | Hierarchies of concepts are useful in many applications from navigation to
organization of objects. Usually, a hierarchy is created in a centralized
manner by employing a group of domain experts, a time-consuming and expensive
process. The experts often design one single hierarchy to best explain the
semantic relations... | computer science |
20,227 | Combining Existential Rules and Transitivity: Next Steps | cs.AI | We consider existential rules (aka Datalog+) as a formalism for specifying
ontologies. In recent years, many classes of existential rules have been
exhibited for which conjunctive query (CQ) entailment is decidable. However,
most of these classes cannot express transitivity of binary relations, a
frequently used modell... | computer science |
20,228 | Prefix-Projection Global Constraint for Sequential Pattern Mining | cs.AI | Sequential pattern mining under constraints is a challenging data mining
task. Many efficient ad hoc methods have been developed for mining sequential
patterns, but they are all suffering from a lack of genericity. Recent works
have investigated Constraint Programming (CP) methods, but they are not still
effective beca... | computer science |
20,229 | Explanation of Stagnation at Points that are not Local Optima in
Particle Swarm Optimization by Potential Analysis | cs.AI | Particle Swarm Optimization (PSO) is a nature-inspired meta-heuristic for
solving continuous optimization problems. In the literature, the potential of
the particles of swarm has been used to show that slightly modified PSO
guarantees convergence to local optima. Here we show that under specific
circumstances the unmod... | computer science |
20,230 | Sistem penunjang keputusan kelayakan pemberian pinjaman dengna metode
fuzzy tsukamoto | cs.AI | Decision support systems (DSS) can be used to help settlement issues or
decisions that are semi-structured or structured. The method used is Fuzzy
Tsukamoto. PT Triprima Finance is a company engaged in the service sector
lending with collateral in the form of Motor Vehicle Owner Book or car (reg).
PT. Triprima Finance ... | computer science |
20,231 | On Distributive Subalgebras of Qualitative Spatial and Temporal Calculi | cs.AI | Qualitative calculi play a central role in representing and reasoning about
qualitative spatial and temporal knowledge. This paper studies distributive
subalgebras of qualitative calculi, which are subalgebras in which (weak)
composition distributives over nonempty intersections. It has been proven for
RCC5 and RCC8 th... | computer science |
20,232 | Desirability and the birth of incomplete preferences | cs.AI | We establish an equivalence between two seemingly different theories: one is
the traditional axiomatisation of incomplete preferences on horse lotteries
based on the mixture independence axiom; the other is the theory of desirable
gambles developed in the context of imprecise probability. The equivalence
allows us to r... | computer science |
20,233 | Stochastic And-Or Grammars: A Unified Framework and Logic Perspective | cs.AI | Stochastic And-Or grammars (AOG) extend traditional stochastic grammars of
language to model other types of data such as images and events. In this paper
we propose a representation framework of stochastic AOGs that is agnostic to
the type of the data being modeled and thus unifies various domain-specific
AOGs. Many ex... | computer science |
20,234 | SkILL - a Stochastic Inductive Logic Learner | cs.AI | Probabilistic Inductive Logic Programming (PILP) is a rel- atively unexplored
area of Statistical Relational Learning which extends classic Inductive Logic
Programming (ILP). This work introduces SkILL, a Stochastic Inductive Logic
Learner, which takes probabilistic annotated data and produces First Order
Logic theorie... | computer science |
20,235 | Performing Bayesian Risk Aggregation using Discrete Approximation
Algorithms with Graph Factorization | cs.AI | Risk aggregation is a popular method used to estimate the sum of a collection
of financial assets or events, where each asset or event is modelled as a
random variable. Applications, in the financial services industry, include
insurance, operational risk, stress testing, and sensitivity analysis, but the
problem is wid... | computer science |
20,236 | A density compensation-based path computing model for measuring semantic
similarity | cs.AI | The shortest path between two concepts in a taxonomic ontology is commonly
used to represent the semantic distance between concepts in the edge-based
semantic similarity measures. In the past, the edge counting is considered to
be the default method for the path computation, which is simple, intuitive and
has low compu... | computer science |
20,237 | Encoding Markov Logic Networks in Possibilistic Logic | cs.AI | Markov logic uses weighted formulas to compactly encode a probability
distribution over possible worlds. Despite the use of logical formulas, Markov
logic networks (MLNs) can be difficult to interpret, due to the often
counter-intuitive meaning of their weights. To address this issue, we propose a
method to construct a... | computer science |
20,238 | Grid-based angle-constrained path planning | cs.AI | Square grids are commonly used in robotics and game development as spatial
models and well known in AI community heuristic search algorithms (such as A*,
JPS, Theta* etc.) are widely used for path planning on grids. A lot of research
is concentrated on finding the shortest (in geometrical sense) paths while in
many app... | computer science |
20,239 | Similarity, Cardinality and Entropy for Bipolar Fuzzy Set in the
Framework of Penta-valued Representation | cs.AI | In this paper one presents new similarity, cardinality and entropy measures
for bipolar fuzzy set and for its particular forms like intuitionistic,
paraconsistent and fuzzy set. All these are constructed in the framework of
multi-valued representations and are based on a penta-valued logic that uses
the following logic... | computer science |
20,240 | Entropy and Syntropy in the Context of Five-Valued Logics | cs.AI | This paper presents a five-valued representation of bifuzzy sets. This
representation is related to a five-valued logic that uses the following
values: true, false, inconsistent, incomplete and ambiguous. In the framework
of five-valued representation, formulae for similarity, entropy and syntropy of
bifuzzy sets are c... | computer science |
20,241 | A Real-time Cargo Damage Management System via a Sorting Array
Triangulation Technique | cs.AI | This report covers an intelligent decision support system (IDSS), which
handles an efficient and effective way to rapidly inspect containerized cargos
for defection. Defection is either cargo exposure to radiation, physical
damages such as holes, punctured surfaces, iron surface oxidation, etc. The
system uses a sortin... | computer science |
20,242 | On SAT Models Enumeration in Itemset Mining | cs.AI | Frequent itemset mining is an essential part of data analysis and data
mining. Recent works propose interesting SAT-based encodings for the problem of
discovering frequent itemsets. Our aim in this work is to define strategies for
adapting SAT solvers to such encodings in order to improve models enumeration.
In this co... | computer science |
20,243 | New Limits for Knowledge Compilation and Applications to Exact Model
Counting | cs.AI | We show new limits on the efficiency of using current techniques to make
exact probabilistic inference for large classes of natural problems. In
particular we show new lower bounds on knowledge compilation to SDD and DNNF
forms. We give strong lower bounds on the complexity of SDD representations by
relating SDD size t... | computer science |
20,244 | Arguments for the Effectiveness of Human Problem Solving | cs.AI | The question of how humans solve problem has been addressed extensively.
However, the direct study of the effectiveness of this process seems to be
overlooked. In this paper, we address the issue of the effectiveness of human
problem solving: we analyze where this effectiveness comes from and what
cognitive mechanisms ... | computer science |
20,245 | On-the-Job Learning with Bayesian Decision Theory | cs.AI | Our goal is to deploy a high-accuracy system starting with zero training
examples. We consider an "on-the-job" setting, where as inputs arrive, we use
real-time crowdsourcing to resolve uncertainty where needed and output our
prediction when confident. As the model improves over time, the reliance on
crowdsourcing quer... | computer science |
20,246 | Bootstrapping Skills | cs.AI | The monolithic approach to policy representation in Markov Decision Processes
(MDPs) looks for a single policy that can be represented as a function from
states to actions. For the monolithic approach to succeed (and this is not
always possible), a complex feature representation is often necessary since the
policy is a... | computer science |
20,247 | Leading Tree in DPCLUS and Its Impact on Building Hierarchies | cs.AI | This paper reveals the tree structure as an intermediate result of clustering
by fast search and find of density peaks (DPCLUS), and explores the power of
using this tree to perform hierarchical clustering. The array used to hold the
index of the nearest higher-densitied object for each object can be transformed
into a... | computer science |
20,248 | Attacker and Defender Counting Approach for Abstract Argumentation | cs.AI | In Dung's abstract argumentation, arguments are either acceptable or
unacceptable, given a chosen notion of acceptability. This gives a coarse way
to compare arguments. In this paper, we propose a counting approach for a more
fine-gained assessment to arguments by counting the number of their respective
attackers and d... | computer science |
20,249 | Artificial general intelligence through recursive data compression and
grounded reasoning: a position paper | cs.AI | This paper presents a tentative outline for the construction of an
artificial, generally intelligent system (AGI). It is argued that building a
general data compression algorithm solving all problems up to a complexity
threshold should be the main thrust of research. A measure for partial progress
in AGI is suggested. ... | computer science |
20,250 | The Scope and Limits of Simulation in Cognitive Models | cs.AI | It has been proposed that human physical reasoning consists largely of
running "physics engines in the head" in which the future trajectory of the
physical system under consideration is computed precisely using accurate
scientific theories. In such models, uncertainty and incomplete knowledge is
dealt with by sampling ... | computer science |
20,251 | HuTO: an Human Time Ontology for Semantic Web Applications | cs.AI | The temporal phenomena have many facets that are studied by different
communities. In Semantic Web, large heterogeneous data are handled and
produced. These data often have informal, semi-formal or formal temporal
information which must be interpreted by software agents. In this paper we
present Human Time Ontology (Hu... | computer science |
20,252 | Sequential Extensions of Causal and Evidential Decision Theory | cs.AI | Moving beyond the dualistic view in AI where agent and environment are
separated incurs new challenges for decision making, as calculation of expected
utility is no longer straightforward. The non-dualistic decision theory
literature is split between causal decision theory and evidential decision
theory. We extend thes... | computer science |
20,253 | Argumentation Semantics for Prioritised Default Logic | cs.AI | We endow prioritised default logic (PDL) with argumentation semantics using
the ASPIC+ framework for structured argumentation, and prove that the
conclusions of the justified arguments are exactly the prioritised default
extensions. Argumentation semantics for PDL will allow for the application of
argument game proof t... | computer science |
20,254 | Characterization of Logic Program Revision as an Extension of
Propositional Revision | cs.AI | We address the problem of belief revision of logic programs, i.e., how to
incorporate to a logic program P a new logic program Q. Based on the structure
of SE interpretations, Delgrande et al. adapted the well-known AGM framework to
logic program (LP) revision. They identified the rational behavior of LP
revision and i... | computer science |
20,255 | A Tool for Computing and Estimating the Volume of the Solution Space of
SMT(LA) | cs.AI | There are already quite a few tools for solving the Satisfiability Modulo
Theories (SMT) problems. In this paper, we present \texttt{VolCE}, a tool for
counting the solutions of SMT constraints, or in other words, for computing the
volume of the solution space. Its input is essentially a set of Boolean
combinations of ... | computer science |
20,256 | Using Monte Carlo method for searching partitionings of hard variants of
Boolean satisfiability problem | cs.AI | In this paper we propose the approach for constructing partitionings of hard
variants of the Boolean satisfiability problem (SAT). Such partitionings can be
used for solving corresponding SAT instances in parallel. For the same SAT
instance one can construct different partitionings, each of them is a set of
simplified ... | computer science |
20,257 | The method of artificial systems | cs.AI | This document is written with the intention to describe in detail a method
and means by which a computer program can reason about the world and in so
doing, increase its analogue to a living system. As the literature is rife and
it is apparent we, as scientists and engineers, have not found the solution,
this document ... | computer science |
20,258 | Latent Belief Theory and Belief Dependencies: A Solution to the Recovery
Problem in the Belief Set Theories | cs.AI | The AGM recovery postulate says: assume a set of propositions X; assume that
it is consistent and that it is closed under logical consequences; remove a
belief P from the set minimally, but make sure that the resultant set is again
some set of propositions X' which is closed under the logical consequences; now
add P ag... | computer science |
20,259 | Toward Idealized Decision Theory | cs.AI | This paper motivates the study of decision theory as necessary for aligning
smarter-than-human artificial systems with human interests. We discuss the
shortcomings of two standard formulations of decision theory, and demonstrate
that they cannot be used to describe an idealized decision procedure suitable
for approxima... | computer science |
20,260 | Towards Log-Linear Logics with Concrete Domains | cs.AI | We present $\mathcal{MEL}^{++}$ (M denotes Markov logic networks) an
extension of the log-linear description logics $\mathcal{EL}^{++}$-LL with
concrete domains, nominals, and instances. We use Markov logic networks (MLNs)
in order to find the most probable, classified and coherent $\mathcal{EL}^{++}$
ontology from an ... | computer science |
20,261 | Lazy Explanation-Based Approximation for Probabilistic Logic Programming | cs.AI | We introduce a lazy approach to the explanation-based approximation of
probabilistic logic programs. It uses only the most significant part of the
program when searching for explanations. The result is a fast and anytime
approximate inference algorithm which returns hard lower and upper bounds on
the exact probability.... | computer science |
20,262 | First-order integer programming for MAP problems | cs.AI | Finding the most probable (MAP) model in SRL frameworks such as Markov logic
and Problog can, in principle, be solved by encoding the problem as a
`grounded-out' mixed integer program (MIP). However, useful first-order
structure disappears in this process motivating the development of first-order
MIP approaches. Here w... | computer science |
20,263 | Ontology Matching with Knowledge Rules | cs.AI | Ontology matching is the process of automatically determining the semantic
equivalences between the concepts of two ontologies. Most ontology matching
algorithms are based on two types of strategies: terminology-based strategies,
which align concepts based on their names or descriptions, and structure-based
strategies,... | computer science |
20,264 | Using Bayesian Network Representations for Effective Sampling from
Generative Network Models | cs.AI | Bayesian networks (BNs) are used for inference and sampling by exploiting
conditional independence among random variables. Context specific independence
(CSI) is a property of graphical models where additional independence relations
arise in the context of particular values of random variables (RVs).
Identifying and ex... | computer science |
20,265 | A Probabilistic Approach to Knowledge Translation | cs.AI | In this paper, we focus on a novel knowledge reuse scenario where the
knowledge in the source schema needs to be translated to a semantically
heterogeneous target schema. We refer to this task as "knowledge translation"
(KT). Unlike data translation and transfer learning, KT does not require any
data from the source or... | computer science |
20,266 | Use of the Triangular Fuzzy Numbers for Student Assessment | cs.AI | In an earlier work we have used the Triangular Fuzzy Numbers (TFNs)as an
assessment tool of student skills.This approach led to an approximate
linguistic characterization of the students' overall performance, but it was
not proved to be sufficient in all cases for comparing the performance of two
different student grou... | computer science |
20,267 | Experimental analysis of data-driven control for a building heating
system | cs.AI | Driven by the opportunity to harvest the flexibility related to building
climate control for demand response applications, this work presents a
data-driven control approach building upon recent advancements in reinforcement
learning. More specifically, model assisted batch reinforcement learning is
applied to the setti... | computer science |
20,268 | Fuzzy Answer Set Computation via Satisfiability Modulo Theories | cs.AI | Fuzzy answer set programming (FASP) combines two declarative frameworks,
answer set programming and fuzzy logic, in order to model reasoning by default
over imprecise information. Several connectives are available to combine
different expressions; in particular the \Godel and \Luka fuzzy connectives are
usually conside... | computer science |
20,269 | Complexity and Compilation of GZ-Aggregates in Answer Set Programming | cs.AI | Gelfond and Zhang recently proposed a new stable model semantics based on
Vicious Circle Principle in order to improve the interpretation of logic
programs with aggregates. The paper focuses on this proposal, and analyzes the
complexity of both coherence testing and cautious reasoning under the new
semantics. Some surp... | computer science |
20,270 | Rewriting recursive aggregates in answer set programming: back to
monotonicity | cs.AI | Aggregation functions are widely used in answer set programming for
representing and reasoning on knowledge involving sets of objects collectively.
Current implementations simplify the structure of programs in order to optimize
the overall performance. In particular, aggregates are rewritten into simpler
forms known as... | computer science |
20,271 | Planning as Tabled Logic Programming | cs.AI | This paper describes Picat's planner, its implementation, and planning models
for several domains used in International Planning Competition (IPC) 2014.
Picat's planner is implemented by use of tabling. During search, every state
encountered is tabled, and tabled states are used to effectively perform
resource-bounded ... | computer science |
20,272 | Evidential relational clustering using medoids | cs.AI | In real clustering applications, proximity data, in which only pairwise
similarities or dissimilarities are known, is more general than object data, in
which each pattern is described explicitly by a list of attributes.
Medoid-based clustering algorithms, which assume the prototypes of classes are
objects, are of great... | computer science |
20,273 | Optimizing the computation of overriding | cs.AI | We introduce optimization techniques for reasoning in DLN---a recently
introduced family of nonmonotonic description logics whose characterizing
features appear well-suited to model the applicative examples naturally arising
in biomedical domains and semantic web access control policies. Such
optimizations are validate... | computer science |
20,274 | A Brain-like Cognitive Process with Shared Methods | cs.AI | This paper describes a new entropy-style of equation that may be useful in a
general sense, but can be applied to a cognitive model with related processes.
The model is based on the human brain, with automatic and distributed pattern
activity. Methods for carrying out the different processes are suggested. The
main pur... | computer science |
20,275 | Human Gender Classification: A Review | cs.AI | Gender contains a wide range of information regarding to the characteristics
difference between male and female. Successful gender recognition is essential
and critical for many applications in the commercial domains such as
applications of human-computer interaction and computer-aided physiological or
psychological an... | computer science |
20,276 | Reinforcement Learning for the Unit Commitment Problem | cs.AI | In this work we solve the day-ahead unit commitment (UC) problem, by
formulating it as a Markov decision process (MDP) and finding a low-cost policy
for generation scheduling. We present two reinforcement learning algorithms,
and devise a third one. We compare our results to previous work that uses
simulated annealing ... | computer science |
20,277 | An Efficient Genetic Algorithm for Discovering Diverse-Frequent Patterns | cs.AI | Working with exhaustive search on large dataset is infeasible for several
reasons. Recently, developed techniques that made pattern set mining feasible
by a general solver with long execution time that supports heuristic search and
are limited to small datasets only. In this paper, we investigate an approach
which aims... | computer science |
20,278 | Adapting Stochastic Search For Real-time Dynamic Weighted Constraint
Satisfaction | cs.AI | This work presents two new algorithms for performing constraint satisfaction.
The first algorithm presented, DMaxWalkSat, is a constraint solver specialized
for solving dynamic, weighted constraint satisfaction problems. The second
algorithm, RDMaxWalkSat, is a derivative of DMaxWalkSat that has been modified
into an a... | computer science |
20,279 | Mapping Big Data into Knowledge Space with Cognitive
Cyber-Infrastructure | cs.AI | Big data research has attracted great attention in science, technology,
industry and society. It is developing with the evolving scientific paradigm,
the fourth industrial revolution, and the transformational innovation of
technologies. However, its nature and fundamental challenge have not been
recognized, and its own... | computer science |
20,280 | Learning Weak Constraints in Answer Set Programming | cs.AI | This paper contributes to the area of inductive logic programming by
presenting a new learning framework that allows the learning of weak
constraints in Answer Set Programming (ASP). The framework, called Learning
from Ordered Answer Sets, generalises our previous work on learning ASP
programs without weak constraints,... | computer science |
20,281 | Improved Answer-Set Programming Encodings for Abstract Argumentation | cs.AI | The design of efficient solutions for abstract argumentation problems is a
crucial step towards advanced argumentation systems. One of the most prominent
approaches in the literature is to use Answer-Set Programming (ASP) for this
endeavor. In this paper, we present new encodings for three prominent
argumentation seman... | computer science |
20,282 | The Digital Synaptic Neural Substrate: A New Approach to Computational
Creativity | cs.AI | We introduce a new artificial intelligence (AI) approach called, the 'Digital
Synaptic Neural Substrate' (DSNS). It uses selected attributes from objects in
various domains (e.g. chess problems, classical music, renowned artworks) and
recombines them in such a way as to generate new attributes that can then, in
princip... | computer science |
20,283 | Unification of Fusion Theories, Rules, Filters, Image Fusion and Target
Tracking Methods (UFT) | cs.AI | The author has pledged in various papers, conference or seminar
presentations, and scientific grant applications (between 2004-2015) for the
unification of fusion theories, combinations of fusion rules, image fusion
procedures, filter algorithms, and target tracking methods for more accurate
applications to our real wo... | computer science |
20,284 | Projected Model Counting | cs.AI | Model counting is the task of computing the number of assignments to
variables V that satisfy a given propositional theory F. Model counting is an
essential tool in probabilistic reasoning. In this paper, we introduce the
problem of model counting projected on a subset P of original variables that we
call 'priority' va... | computer science |
20,285 | Scaling up Greedy Causal Search for Continuous Variables | cs.AI | As standardly implemented in R or the Tetrad program, causal search
algorithms used most widely or effectively by scientists have severe
dimensionality constraints that make them inappropriate for big data problems
without sacrificing accuracy. However, implementation improvements are
possible. We explore optimizations... | computer science |
20,286 | Communication: Words and Conceptual Systems | cs.AI | Words (phrases or symbols) play a key role in human life. Word (phrase or
symbol) representation is the fundamental problem for knowledge representation
and understanding. A word (phrase or symbol) usually represents a name of a
category. However, it is always a challenge that how to represent a category
can make it ea... | computer science |
20,287 | Optimal estimates for short horizon travel time prediction in urban
areas | cs.AI | Increasing popularity of mobile route planning applications based on GPS
technology provides opportunities for collecting traffic data in urban
environments. One of the main challenges for travel time estimation and
prediction in such a setting is how to aggregate data from vehicles that have
followed different routes,... | computer science |
20,288 | CRISNER: A Practically Efficient Reasoner for Qualitative Preferences | cs.AI | We present CRISNER (Conditional & Relative Importance Statement Network
PrEference Reasoner), a tool that provides practically efficient as well as
exact reasoning about qualitative preferences in popular ceteris paribus
preference languages such as CP-nets, TCP-nets, CP-theories, etc. The tool uses
a model checking en... | computer science |
20,289 | Studying a set of properties of inconsistency indices for pairwise
comparisons | cs.AI | Pairwise comparisons between alternatives are a well-established tool to
decompose decision problems into smaller and more easily tractable
sub-problems. However, due to our limited rationality, the subjective
preferences expressed by decision makers over pairs of alternatives can hardly
ever be consistent. Therefore, ... | computer science |
20,290 | A Minimal Architecture for General Cognition | cs.AI | A minimalistic cognitive architecture called MANIC is presented. The MANIC
architecture requires only three function approximating models, and one state
machine. Even with so few major components, it is theoretically sufficient to
achieve functional equivalence with all other cognitive architectures, and can
be practic... | computer science |
20,291 | Procedural Content Generation for GDL Descriptions of Simplified
Boardgames | cs.AI | We present initial research towards procedural generation of Simplified
Boardgames and translating them into an efficient GDL code. This is a step
towards establishing Simplified Boardgames as a comparison class for General
Game Playing agents. To generate playable, human readable, and balanced
chess-like games we use ... | computer science |
20,292 | Learning from Pairwise Marginal Independencies | cs.AI | We consider graphs that represent pairwise marginal independencies amongst a
set of variables (for instance, the zero entries of a covariance matrix for
normal data). We characterize the directed acyclic graphs (DAGs) that
faithfully explain a given set of independencies, and derive algorithms to
efficiently enumerate ... | computer science |
20,293 | Using Behavior Objects to Manage Complexity in Virtual Worlds | cs.AI | The quality of high-level AI of non-player characters (NPCs) in commercial
open-world games (OWGs) has been increasing during the past years. However, due
to constraints specific to the game industry, this increase has been slow and
it has been driven by larger budgets rather than adoption of new complex AI
techniques.... | computer science |
20,294 | Identifying Avatar Aliases in Starcraft 2 | cs.AI | In electronic sports, cyberathletes conceal their online training using
different avatars (virtual identities), allowing them not being recognized by
the opponents they may face in future competitions. In this article, we propose
a method to tackle this avatar aliases identification problem. Our method
trains a classif... | computer science |
20,295 | Qualitative Decision Methods for Multi-Attribute Decision Making | cs.AI | The fundamental problem underlying all multi-criteria decision analysis
(MCDA) problems is that of dominance between any two alternatives: "Given two
alternatives A and B, each described by a set criteria, is A preferred to B
with respect to a set of decision maker (DM) preferences over the criteria?".
Depending on the... | computer science |
20,296 | On the Linear Belief Compression of POMDPs: A re-examination of current
methods | cs.AI | Belief compression improves the tractability of large-scale partially
observable Markov decision processes (POMDPs) by finding projections from
high-dimensional belief space onto low-dimensional approximations, where
solving to obtain action selection policies requires fewer computations. This
paper develops a unified ... | computer science |
20,297 | A different perspective on a scale for pairwise comparisons | cs.AI | One of the major challenges for collective intelligence is inconsistency,
which is unavoidable whenever subjective assessments are involved. Pairwise
comparisons allow one to represent such subjective assessments and to process
them by analyzing, quantifying and identifying the inconsistencies.
We propose using small... | computer science |
20,298 | Sufficient and necessary conditions for Dynamic Programming in
Valuation-Based Systems | cs.AI | Valuation algebras abstract a large number of formalisms for automated
reasoning and enable the definition of generic inference procedures. Many of
these formalisms provide some notion of solution. Typical examples are
satisfying assignments in constraint systems, models in logics or solutions to
linear equation system... | computer science |
20,299 | Fuzzy Longest Common Subsequence Matching With FCM Using R | cs.AI | Capturing the interdependencies between real valued time series can be
achieved by finding common similar patterns. The abstraction of time series
makes the process of finding similarities closer to the way as humans do.
Therefore, the abstraction by means of a symbolic levels and finding the common
patterns attracts r... | computer science |
20,300 | Causal Decision Trees | cs.AI | Uncovering causal relationships in data is a major objective of data
analytics. Causal relationships are normally discovered with designed
experiments, e.g. randomised controlled trials, which, however are expensive or
infeasible to be conducted in many cases. Causal relationships can also be
found using some well desi... | computer science |
20,301 | From Observational Studies to Causal Rule Mining | cs.AI | Randomised controlled trials (RCTs) are the most effective approach to causal
discovery, but in many circumstances it is impossible to conduct RCTs.
Therefore observational studies based on passively observed data are widely
accepted as an alternative to RCTs. However, in observational studies, prior
knowledge is requi... | computer science |
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