The Experts below are selected from a list of 3315 Experts worldwide ranked by ideXlab platform
Adrian R. Pearce - One of the best experts on this subject based on the ideXlab platform.
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property persistence in the situation calculus
Artificial Intelligence, 2010Co-Authors: Ryan F Kelly, Adrian R. PearceAbstract:We develop a new automated reasoning technique for the situation calculus that can handle a class of queries containing Universal Quantification over situation terms. Although such queries arise naturally in many important reasoning tasks, they are difficult to automate in the situation calculus due to the presence of a second-order induction axiom. We show how to reduce queries about property persistence, a common type of Universally-quantified query, to an equivalent form that does not quantify over situations and so is amenable to existing reasoning techniques. Our algorithm replaces induction with a meta-level fixpoint calculation; crucially, this calculation uses only first-order reasoning with a limited set of axioms. The result is a powerful new tool for verifying sophisticated domain properties in the situation calculus.
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property persistence in the situation calculus
International Joint Conference on Artificial Intelligence, 2007Co-Authors: Ryan F Kelly, Adrian R. PearceAbstract:We develop an algorithm for reducing Universally quantified situation calculus queries to a form more amenable to automated reasoning. Universal Quantification in the situation calculus requires a second-order induction axiom, making automated reasoning difficult for such queries. We show how to reduce queries about property persistence, a common family of Universally-quantified query, to an equivalent form that does not quantify over situations. The algorithm for doing so utilizes only first-order reasoning. We give several examples of important reasoning tasks that are facilitated by our approach, including checking for goal impossibility and reasoning about knowledge with partial observability of actions.
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IJCAI - Property persistence in the situation calculus
2007Co-Authors: Ryan F Kelly, Adrian R. PearceAbstract:We develop an algorithm for reducing Universally quantified situation calculus queries to a form more amenable to automated reasoning. Universal Quantification in the situation calculus requires a second-order induction axiom, making automated reasoning difficult for such queries. We show how to reduce queries about property persistence, a common family of Universally-quantified query, to an equivalent form that does not quantify over situations. The algorithm for doing so utilizes only first-order reasoning. We give several examples of important reasoning tasks that are facilitated by our approach, including checking for goal impossibility and reasoning about knowledge with partial observability of actions.
Ryan F Kelly - One of the best experts on this subject based on the ideXlab platform.
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property persistence in the situation calculus
Artificial Intelligence, 2010Co-Authors: Ryan F Kelly, Adrian R. PearceAbstract:We develop a new automated reasoning technique for the situation calculus that can handle a class of queries containing Universal Quantification over situation terms. Although such queries arise naturally in many important reasoning tasks, they are difficult to automate in the situation calculus due to the presence of a second-order induction axiom. We show how to reduce queries about property persistence, a common type of Universally-quantified query, to an equivalent form that does not quantify over situations and so is amenable to existing reasoning techniques. Our algorithm replaces induction with a meta-level fixpoint calculation; crucially, this calculation uses only first-order reasoning with a limited set of axioms. The result is a powerful new tool for verifying sophisticated domain properties in the situation calculus.
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property persistence in the situation calculus
International Joint Conference on Artificial Intelligence, 2007Co-Authors: Ryan F Kelly, Adrian R. PearceAbstract:We develop an algorithm for reducing Universally quantified situation calculus queries to a form more amenable to automated reasoning. Universal Quantification in the situation calculus requires a second-order induction axiom, making automated reasoning difficult for such queries. We show how to reduce queries about property persistence, a common family of Universally-quantified query, to an equivalent form that does not quantify over situations. The algorithm for doing so utilizes only first-order reasoning. We give several examples of important reasoning tasks that are facilitated by our approach, including checking for goal impossibility and reasoning about knowledge with partial observability of actions.
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IJCAI - Property persistence in the situation calculus
2007Co-Authors: Ryan F Kelly, Adrian R. PearceAbstract:We develop an algorithm for reducing Universally quantified situation calculus queries to a form more amenable to automated reasoning. Universal Quantification in the situation calculus requires a second-order induction axiom, making automated reasoning difficult for such queries. We show how to reduce queries about property persistence, a common family of Universally-quantified query, to an equivalent form that does not quantify over situations. The algorithm for doing so utilizes only first-order reasoning. We give several examples of important reasoning tasks that are facilitated by our approach, including checking for goal impossibility and reasoning about knowledge with partial observability of actions.
Orna Kupferman - One of the best experts on this subject based on the ideXlab platform.
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Alternating-time temporal logic
Proceedings 38th Annual Symposium on Foundations of Computer Science, 2002Co-Authors: Rajeev Alur, Thomas A. Henzinger, Orna KupfermanAbstract:Temporal logic comes in two varieties: linear-time temporal logic assumes implicit Universal Quantification over all paths that are generated by the execution of a system; branching-time temporal logic allows explicit existential and Universal Quantification over all paths. We introduce a third, more general variety of temporal logic: alternating-time temporal logic offers selective Quantification over those paths that are possible outcomes of games, such as the game in which the system and the environment alternate moves. While linear-time and branching-time logics are natural specification languages for closed systems, alternating-time logics are natural specification languages for open systems. For example, by preceding the temporal operator "eventually" with a selective path quantifier, we can specify that in the game between the system and the environment, the system has a strategy to reach a certain state. The problems of receptiveness, realizability, and controllability can be formulated as model-checking problems for alternating-time formulas. Depending on whether or not we admit arbitrary nesting of selective path quantifiers and temporal operators, we obtain the two alternating-time temporal logics ATL and ATL*.ATL and ATL* are interpreted over concurrent game structures. Every state transition of a concurrent game structure results from a choice of moves, one for each player. The players represent individual components and the environment of an open system. Concurrent game structures can capture various forms of synchronous composition for open systems, and if augmented with fairness constraints, also asynchronous composition. Over structures without fairness constraints, the model-checking complexity of ATL is linear in the size of the game structure and length of the formula, and the symbolic model-checking algorithm for CTL extends with few modifications to ATL. Over structures with weak-fairness constraints, ATL model checking requires the solution of 1-pair Rabin games, and can be done in polynomial time. Over structures with strong-fairness constraints, ATL model checking requires the solution of games with Boolean combinations of Büchi conditions, and can be done in PSPACE. In the case of ATL*, the model-checking problem is closely related to the synthesis problem for linear-time formulas, and requires doubly exponential time.
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Alternating-time temporal logic
Proceedings 38th Annual Symposium on Foundations of Computer Science, 1997Co-Authors: Rajeev Alur, Thomas A. Henzinger, Orna KupfermanAbstract:Temporal logic comes in two varieties: linear-time temporal logic assumes implicit Universal Quantification over all paths that are generated by system moves; branching-time temporal logic allows explicit existential and Universal Quantification over all paths. We introduce a third, more general variety of temporal logic: alternating-time temporal logic offers selective Quantification over those paths that are possible outcomes of games, such as the game in which the system and the environment alternate moves. While linear-time and branching-time logics are natural specification languages for closed systems, alternating-time logics are natural specification languages for open systems. For example, by preceding the temporal operator "eventually" with a selective path quantifier, we can specify that in the game between the system and the environment, the system has a strategy to reach a certain state. Also the problems of receptiveness, realizability, and controllability can be formulated as model-checking problems for alternating-time formulas.
Renaud De Landtsheer - One of the best experts on this subject based on the ideXlab platform.
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solving csp including a Universal Quantification
Lecture Notes in Computer Science, 2004Co-Authors: Renaud De LandtsheerAbstract:This paper presents a method to solve constraint satisfaction problems including a Universally quantified variable with finite domain. Similar problems appear in the field of bounded model checking. The presented method is built on top of the Mozart constraint programming platform. The main principle of the algorithm is to consider only representative values in the domain of the quantified variable. The presented algorithm is similar to a branch and bound search. Significant improvements have been achieved both in memory consumption and execution time compared to a naive approach.
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MOZ - Solving CSP including a Universal Quantification
Lecture Notes in Computer Science, 2004Co-Authors: Renaud De LandtsheerAbstract:This paper presents a method to solve constraint satisfaction problems including a Universally quantified variable with finite domain. Similar problems appear in the field of bounded model checking. The presented method is built on top of the Mozart constraint programming platform. The main principle of the algorithm is to consider only representative values in the domain of the quantified variable. The presented algorithm is similar to a branch and bound search. Significant improvements have been achieved both in memory consumption and execution time compared to a naive approach.
Rajeev Alur - One of the best experts on this subject based on the ideXlab platform.
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Alternating-time temporal logic
Proceedings 38th Annual Symposium on Foundations of Computer Science, 2002Co-Authors: Rajeev Alur, Thomas A. Henzinger, Orna KupfermanAbstract:Temporal logic comes in two varieties: linear-time temporal logic assumes implicit Universal Quantification over all paths that are generated by the execution of a system; branching-time temporal logic allows explicit existential and Universal Quantification over all paths. We introduce a third, more general variety of temporal logic: alternating-time temporal logic offers selective Quantification over those paths that are possible outcomes of games, such as the game in which the system and the environment alternate moves. While linear-time and branching-time logics are natural specification languages for closed systems, alternating-time logics are natural specification languages for open systems. For example, by preceding the temporal operator "eventually" with a selective path quantifier, we can specify that in the game between the system and the environment, the system has a strategy to reach a certain state. The problems of receptiveness, realizability, and controllability can be formulated as model-checking problems for alternating-time formulas. Depending on whether or not we admit arbitrary nesting of selective path quantifiers and temporal operators, we obtain the two alternating-time temporal logics ATL and ATL*.ATL and ATL* are interpreted over concurrent game structures. Every state transition of a concurrent game structure results from a choice of moves, one for each player. The players represent individual components and the environment of an open system. Concurrent game structures can capture various forms of synchronous composition for open systems, and if augmented with fairness constraints, also asynchronous composition. Over structures without fairness constraints, the model-checking complexity of ATL is linear in the size of the game structure and length of the formula, and the symbolic model-checking algorithm for CTL extends with few modifications to ATL. Over structures with weak-fairness constraints, ATL model checking requires the solution of 1-pair Rabin games, and can be done in polynomial time. Over structures with strong-fairness constraints, ATL model checking requires the solution of games with Boolean combinations of Büchi conditions, and can be done in PSPACE. In the case of ATL*, the model-checking problem is closely related to the synthesis problem for linear-time formulas, and requires doubly exponential time.
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Alternating-time temporal logic
Proceedings 38th Annual Symposium on Foundations of Computer Science, 1997Co-Authors: Rajeev Alur, Thomas A. Henzinger, Orna KupfermanAbstract:Temporal logic comes in two varieties: linear-time temporal logic assumes implicit Universal Quantification over all paths that are generated by system moves; branching-time temporal logic allows explicit existential and Universal Quantification over all paths. We introduce a third, more general variety of temporal logic: alternating-time temporal logic offers selective Quantification over those paths that are possible outcomes of games, such as the game in which the system and the environment alternate moves. While linear-time and branching-time logics are natural specification languages for closed systems, alternating-time logics are natural specification languages for open systems. For example, by preceding the temporal operator "eventually" with a selective path quantifier, we can specify that in the game between the system and the environment, the system has a strategy to reach a certain state. Also the problems of receptiveness, realizability, and controllability can be formulated as model-checking problems for alternating-time formulas.
