The Experts below are selected from a list of 26262 Experts worldwide ranked by ideXlab platform
Charles Gretton - One of the best experts on this subject based on the ideXlab platform.
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a more Expressive behavioral Logic for decision theoretic planning
Pacific Rim International Conference on Artificial Intelligence, 2014Co-Authors: Charles GrettonAbstract:We examine the problem of compactly expressing models of non-Markovian reward decision processes (NMRDP). In the field of decision-theoretic planning NMRDPs are used whenever the agent’s reward is determined by the history of visited states. Two different propositional linear temporal Logics can be used to describe execution histories that are rewarding. Called PLTL and $FLTL, they are backward and forward looking Logics respectively. In this paper we find both to be Expressively weak and propose a change to $FLTL resulting in a much more Expressive Logic that we have called $* FLTL. The time complexities of $* FLTL and $FLTL related model checking operations performed in planning are the same.
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PRICAI - A More Expressive Behavioral Logic for Decision-Theoretic Planning
Lecture Notes in Computer Science, 2014Co-Authors: Charles GrettonAbstract:We examine the problem of compactly expressing models of non-Markovian reward decision processes (NMRDP). In the field of decision-theoretic planning NMRDPs are used whenever the agent’s reward is determined by the history of visited states. Two different propositional linear temporal Logics can be used to describe execution histories that are rewarding. Called PLTL and $FLTL, they are backward and forward looking Logics respectively. In this paper we find both to be Expressively weak and propose a change to $FLTL resulting in a much more Expressive Logic that we have called $* FLTL. The time complexities of $* FLTL and $FLTL related model checking operations performed in planning are the same.
Ian Horrocks - One of the best experts on this subject based on the ideXlab platform.
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A Tableau Decision Procedure for $\mathcal{SHOIQ}$
Journal of Automated Reasoning, 2007Co-Authors: Ian Horrocks, Ulrike SattlerAbstract:OWL DL, a new W3C ontology language recommendation, is based on the Expressive description Logic $\mathcal{SHOIN}$ . Although the ontology consistency problem for $\mathcal{SHOIN}$ is known to be decidable, up to now there has been no known “practical” decision procedure, that is, a goal-directed procedure that is likely to perform well with realistic ontology derived problems. We present such a decision procedure for $\mathcal{SHOIQ}$ , a slightly more Expressive Logic than $\mathcal{SHOIN}$ , extending the well-known algorithm for $\mathcal{SHIQ}$ , which is the basis for several highly successful implementations.
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a tableau decision procedure for mathcal shoiq
Journal of Automated Reasoning, 2007Co-Authors: Ian Horrocks, Ulrike SattlerAbstract:OWL DL, a new W3C ontology language recommendation, is based on the Expressive description Logic $\mathcal{SHOIN}$ . Although the ontology consistency problem for $\mathcal{SHOIN}$ is known to be decidable, up to now there has been no known "practical" decision procedure, that is, a goal-directed procedure that is likely to perform well with realistic ontology derived problems. We present such a decision procedure for $\mathcal{SHOIQ}$ , a slightly more Expressive Logic than $\mathcal{SHOIN}$ , extending the well-known algorithm for $\mathcal{SHIQ}$ , which is the basis for several highly successful implementations.
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A Tableau Decision Procedure for $\mathcal{SHOIQ}$
Journal of Automated Reasoning, 2007Co-Authors: Ian Horrocks, Ulrike SattlerAbstract:OWL DL, a new W3C ontology language recommendation, is based on the Expressive description Logic $\mathcal{SHOIN}$ . Although the ontology consistency problem for $\mathcal{SHOIN}$ is known to be decidable, up to now there has been no known "practical" decision procedure, that is, a goal-directed procedure that is likely to perform well with realistic ontology derived problems. We present such a decision procedure for $\mathcal{SHOIQ}$ , a slightly more Expressive Logic than $\mathcal{SHOIN}$ , extending the well-known algorithm for $\mathcal{SHIQ}$ , which is the basis for several highly successful implementations.
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TABLEAUX - Benchmark Analysis with FaCT
Lecture Notes in Computer Science, 2000Co-Authors: Ian HorrocksAbstract:FaCT (Fast Classification of Terminologies) is a Description Logic (DL) classifier that can also be used for modal Logic satisfiability testing. The FaCT system includes two reasoners, one for the Logic \(\mathcal{SHF}\) and the other for the Logic \(\mathcal{SHIQ}\), both of which use optimised implementations of sound and complete tableaux algorithms. FaCT’s most interesting features are its Expressive Logic (in particular the \(\mathcal{SHIQ}\) reasoner), its optimised tableaux implementation (which has now become the standard for DL systems), and its CORBA based client-server architecture.
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Description Logics - FaCT and iFaCT.
Description Logics, 1999Co-Authors: Ian HorrocksAbstract:FaCT (Fast Classification of Terminologies) is a Description Logic (DL) classifier which has been implemented as a test-bed for a sound and complete tableaux satisfiability/subsumption testing algorithm. FaCT’s novelty lies in its relatively Expressive Logic and its highly optimised implementation of the tableaux algorithm. iFaCT is an extension of FaCT that supports reasoning with inverse roles. The resulting Logic is particularly interesting as it no longer has the finite model property.
Nabil Layaïda - One of the best experts on this subject based on the ideXlab platform.
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SPARQL Query Containment under RDFS Entailment Regime
2012Co-Authors: Melisachew Wudage Chekol, Jérôme Euzenat, Pierre Genevès, Nabil LayaïdaAbstract:The problem of SPARQL query containment is defined as determining if the result of one query is included in the result of another for any RDF graph. Query containment is important in many areas, including information integration, query optimization, and reasoning about Entity-Relationship diagrams. We encode this problem into an Expressive Logic called mu-calculus: where RDF graphs become transition systems, queries and schema axioms become formulas. Thus, the containment problem is reduced to formula satisfiability test. Beyond the Logic's Expressive power, satisfiability solvers are available for it. Hence, this study allows to exploit these advantages.
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IJCAR - SPARQL query containment under RDFS entailment regime
Automated Reasoning, 2012Co-Authors: Melisachew Wudage Chekol, Pierre Genevès, Jérôme Euzenat, Nabil LayaïdaAbstract:The problem of SPARQL query containment is defined as determining if the result of one query is included in the result of another for any RDF graph. Query containment is important in many areas, including information integration, query optimization, and reasoning about Entity-Relationship diagrams. We encode this problem into an Expressive Logic called μ-calculus: where RDF graphs become transition systems, queries and schema axioms become formulas. Thus, the containment problem is reduced to formula satisfiability test. Beyond the Logic's Expressive power, satisfiability solvers are available for it. Hence, this study allows to exploit these advantages.
Mark Reynolds - One of the best experts on this subject based on the ideXlab platform.
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TABLEAUX - The Mosaic Method for Temporal Logics
Lecture Notes in Computer Science, 2000Co-Authors: Maarten Marx, Szabolcs Mikulás, Mark ReynoldsAbstract:The aim of this paper is to apply the mosaic method for proving complexity, Hilbert-style and tableau completeness results for Prior’s temporal Logic over linear flows of time. We also show how to implement the mosaic idea for automated theorem-proving. Finally we indicate the modifications required to achieve similar results for special linear flows of time and for the more Expressive Logic of until and since.
Aniello Murano - One of the best experts on this subject based on the ideXlab platform.
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KR - Nondeterministic Strategies and their Refinement in Strategy Logic.
Proceedings of the Seventeenth International Conference on Principles of Knowledge Representation and Reasoning, 2020Co-Authors: Giuseppe De Giacomo, Bastien Maubert, Aniello MuranoAbstract:Nondeterministic strategies are strategies (or protocols, or plans) that, given a history in a game, assign a set of possible actions, all of which are winning. An important problem is that of refining such strategies. For instance, given a nondeterministic strategy that allows only safe executions, refine it to, additionally, eventually reach a desired state of affairs. We show that strategic problems involving strategy refinement can be solved elegantly in the framework of Strategy Logic (SL), a very Expressive Logic to reason about strategic abilities. Specifically, we introduce an extension of SL with nondeterministic strategies and an operator expressing strategy refinement. We show that model checking this Logic can be done at no additional computational cost with respect to standard SL, and can be used to solve a variety of problems such as synthesis of maximally permissive strategies or refinement of Nash equilibria.
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reasoning about strategies on the model checking problem
ACM Transactions on Computational Logic, 2014Co-Authors: Fabio Mogavero, Aniello Murano, Giuseppe Perelli, Moshe Y VardiAbstract:In open systems verification, to formally check for reliability, one needs an appropriate formalism to model the interaction between agents and express the correctness of the system no matter how the environment behaves. An important contribution in this context is given by modal Logics for strategic ability, in the setting of multiagent games, such as A tl , A tl *, and the like. Recently, Chatterjee, Henzinger, and Piterman introduced Strategy Logic, which we denote here by CHP-S l , with the aim of getting a powerful framework for reasoning explicitly about strategies. CHP-S l is obtained by using first-order quantifications over strategies and has been investigated in the very specific setting of two-agents turned-based games, where a nonelementary model-checking algorithm has been provided. While CHP-S l is a very Expressive Logic, we claim that it does not fully capture the strategic aspects of multiagent systems. In this article, we introduce and study a more general strategy Logic, denoted S l , for reasoning about strategies in multiagent concurrent games. As a key aspect, strategies in S l are not intrinsically glued to a specific agent, but an explicit binding operator allows an agent to bind to a strategy variable. This allows agents to share strategies or reuse one previously adopted. We prove that S l strictly includes CHP-S l , while maintaining a decidable model-checking problem. In particular, the algorithm we propose is computationally not harder than the best one known for CHP-S l . Moreover, we prove that such a problem for S l is N on E lementary . This negative result has spurred us to investigate syntactic fragments of S l , strictly subsuming A tl *, with the hope of obtaining an elementary model-checking problem. Among others, we introduce and study the subLogics S l [ ng ], S l [ bg ], and S l [1 g ]. They encompass formulas in a special prenex normal form having, respectively, nested temporal goals, Boolean combinations of goals, and, a single goal at a time. Intuitively, for a goal, we mean a sequence of bindings, one for each agent, followed by an L tl formula. We prove that the model-checking problem for S l [1 g ] is 2E xp T ime - complete , thus not harder than the one for A tl *. In contrast, S l [ ng ] turns out to be N on E lementary -hard, strengthening the corresponding result for S l . Regarding S l [ bg ], we show that it includes CHP-S l and its model-checking is decidable with a 2E xp T ime lower-bound. It is worth enlightening that to achieve the positive results about S l [1 g ], we introduce a fundamental property of the semantics of this Logic, called behavioral, which allows to strongly simplify the reasoning about strategies. Indeed, in a nonbehavioral Logic such as S l [ bg ] and the subsuming ones, to satisfy a formula, one has to take into account that a move of an agent, at a given moment of a play, may depend on the moves taken by any agent in another counterfactual play.
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reasoning about strategies on the model checking problem
arXiv: Logic in Computer Science, 2011Co-Authors: Fabio Mogavero, Aniello Murano, Giuseppe Perelli, Moshe Y VardiAbstract:In open systems verification, to formally check for reliability, one needs an appropriate formalism to model the interaction between agents and express the correctness of the system no matter how the environment behaves. An important contribution in this context is given by modal Logics for strategic ability, in the setting of multi-agent games, such as ATL, ATL\star, and the like. Recently, Chatterjee, Henzinger, and Piterman introduced Strategy Logic, which we denote here by CHP-SL, with the aim of getting a powerful framework for reasoning explicitly about strategies. CHP-SL is obtained by using first-order quantifications over strategies and has been investigated in the very specific setting of two-agents turned-based games, where a non-elementary model-checking algorithm has been provided. While CHP-SL is a very Expressive Logic, we claim that it does not fully capture the strategic aspects of multi-agent systems. In this paper, we introduce and study a more general strategy Logic, denoted SL, for reasoning about strategies in multi-agent concurrent games. We prove that SL includes CHP-SL, while maintaining a decidable model-checking problem. In particular, the algorithm we propose is computationally not harder than the best one known for CHP-SL. Moreover, we prove that such a problem for SL is NonElementarySpace-hard. This negative result has spurred us to investigate here syntactic fragments of SL, strictly subsuming ATL\star, with the hope of obtaining an elementary model-checking problem. Among the others, we study the subLogics SL[NG], SL[BG], and SL[1G]. They encompass formulas in a special prenex normal form having, respectively, nested temporal goals, Boolean combinations of goals and, a single goal at a time. About these Logics, we prove that the model-checking problem for SL[1G] is 2ExpTime-complete, thus not harder than the one for ATL\star.
