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350
Classical negation in logic programs and disjunctive databases
 New Generation Computing
, 1991
"... An important limitation of traditional logic programming as a knowledge representation tool, in comparison with classical logic, is that logic programming does not allow us to deal directly with incomplete information. In order to overcome this limitation, we extend the class of general logic progra ..."
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Cited by 1050 (76 self)
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An important limitation of traditional logic programming as a knowledge representation tool, in comparison with classical logic, is that logic programming does not allow us to deal directly with incomplete information. In order to overcome this limitation, we extend the class of general logic programs by including classical negation, in addition to negationasfailure. The semantics of such extended programs is based on the method of stable models. The concept of a disjunctive database can be extended in a similar way. We show that some facts of commonsense knowledge can be represented by logic programs and disjunctive databases more easily when classical negation is available. Computationally, classical negation can be eliminated from extended programs by a simple preprocessor. Extended programs are identical to a special case of default theories in the sense of Reiter. 1
Convex Analysis
, 1970
"... In this book we aim to present, in a unified framework, a broad spectrum of mathematical theory that has grown in connection with the study of problems of optimization, equilibrium, control, and stability of linear and nonlinear systems. The title Variational Analysis reflects this breadth. For a lo ..."
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Cited by 5350 (67 self)
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In this book we aim to present, in a unified framework, a broad spectrum of mathematical theory that has grown in connection with the study of problems of optimization, equilibrium, control, and stability of linear and nonlinear systems. The title Variational Analysis reflects this breadth. For a long time, ‘variational ’ problems have been identified mostly with the ‘calculus of variations’. In that venerable subject, built around the minimization of integral functionals, constraints were relatively simple and much of the focus was on infinitedimensional function spaces. A major theme was the exploration of variations around a point, within the bounds imposed by the constraints, in order to help characterize solutions and portray them in terms of ‘variational principles’. Notions of perturbation, approximation and even generalized differentiability were extensively investigated. Variational theory progressed also to the study of socalled stationary points, critical points, and other indications of singularity that a point might have relative to its neighbors, especially in association with existence theorems for differential equations.
Approximate Solutions for Partially Observable Stochastic Games with Common Payoffs
 In Proc. of Int. Joint Conference on Autonomous Agents and Multi Agent Systems
, 2004
"... Partially observable decentralized decision making in robot teams is fundamentally different from decision making in fully observable problems. Team members cannot simply apply singleagent solution techniques in parallel. Instead, we must turn to game theoretic frameworks to correctly model the pro ..."
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Cited by 92 (2 self)
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discounted value of actions. This algorithm trades off limited lookahead in uncertainty for computational feasibility, and results in policies that are locally optimal with respect to the selected heuristic. Empirical results are provided for both a simple problem for which the full POSG can also
Game theoretic control for robot teams
 In Proc. of the IEEE International Conference on Robotics and Automation
, 2005
"... Abstract — In the real world, noisy sensors and limited communication make it difficult for robot teams to coordinate in tighty coupled tasks. Team members cannot simply apply singlerobot solution techniques for partially observable problems in parallel because they do not take into account the rec ..."
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Cited by 44 (1 self)
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the recursive effect that reasoning about the beliefs of others has on policy generation. Instead, we must turn to a game theoretic approach to model the problem correctly. Partially observable stochastic games (POSGs) provide a solution model for decentralized robot teams, however, this model quickly becomes
Dynamic Programming Approximations for Partially Observable Stochastic Games
"... Partially observable stochastic games (POSGs) provide a rich mathematical framework for planning under uncertainty by a group of agents. However, this modeling advantage comes with a price, namely a high computational cost. Solving POSGs optimally quickly becomes intractable after a few decision cyc ..."
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Cited by 3 (1 self)
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Partially observable stochastic games (POSGs) provide a rich mathematical framework for planning under uncertainty by a group of agents. However, this modeling advantage comes with a price, namely a high computational cost. Solving POSGs optimally quickly becomes intractable after a few decision
Improved memorybounded dynamic programming for decentralized POMDPs
 In Proceedings of the TwentyThird Conference on Uncertainty in Artificial Intelligence
, 2007
"... Decentralized decision making under uncertainty has been shown to be intractable when each agent has different partial information about the domain. Thus, improving the applicability and scalability of planning algorithms is an important challenge. We present the first memorybounded dynamic program ..."
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Cited by 94 (22 self)
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Decentralized decision making under uncertainty has been shown to be intractable when each agent has different partial information about the domain. Thus, improving the applicability and scalability of planning algorithms is an important challenge. We present the first memorybounded dynamic programming algorithm for finitehorizon decentralized POMDPs. A set of heuristics is used to identify relevant points of the infinitely large belief space. Using these belief points, the algorithm successively selects the best joint policies for each horizon. The algorithm is extremely efficient, having linear time and space complexity with respect to the horizon length. Experimental results show that it can handle horizons that are multiple orders of magnitude larger than what was previously possible, while achieving the same or better solution quality. These results significantly increase the applicability of decentralized decisionmaking techniques. 1
General Terms
"... We present the agent programming language POGTGolog, which combines explicit agent programming in Golog with gametheoretic multiagent planning in a special kind of partially observable stochastic games (POSGs). The approach allows for partially specifying a highlevel control program for a system ..."
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We present the agent programming language POGTGolog, which combines explicit agent programming in Golog with gametheoretic multiagent planning in a special kind of partially observable stochastic games (POSGs). The approach allows for partially specifying a highlevel control program for a system
Regular Expressions into Finite Automata
 Theoretical Computer Science
, 1996
"... It is a wellestablished fact that each regular expression can be transformed into a nondeterministic finite automaton (NFA) with or without ffltransitions, and all authors seem to provide their own variant of the construction. Of these, Berry and Sethi [BS86] have shown that the construction of ..."
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Cited by 84 (5 self)
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It is a wellestablished fact that each regular expression can be transformed into a nondeterministic finite automaton (NFA) with or without ffltransitions, and all authors seem to provide their own variant of the construction. Of these, Berry and Sethi [BS86] have shown that the construction of an fflfree NFA due to to Glushkov [Glu61] is a natural representation of the regular expression, because it can be described in terms of the Brzozowski derivatives [Brz64] of the expression. Moreover, the Glushkov construction also plays a significant role in the document processing area: The SGML standard [ISO86], now widely adopted by publishing houses and government agencies for the syntactic specification of textual markup systems, uses deterministic regular expressions, i.e. expressions whose Glushkov automaton is deterministic, as a description language for document types. In this paper, we first show that the Glushkov automaton can be constructed in time quadratic in the size of the...
Disjunctive Logic Programs with Inheritance
 In Procs. of ICLP99
, 1999
"... The paper proposes a new knowledge representation language, called DLP , which extends disjunctive logic programming (with strong negation) by inheritance. The addition of inheritance enhances the knowledge modeling features of the language providing a natural representation of default reasoning wi ..."
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Cited by 77 (7 self)
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The paper proposes a new knowledge representation language, called DLP , which extends disjunctive logic programming (with strong negation) by inheritance. The addition of inheritance enhances the knowledge modeling features of the language providing a natural representation of default reasoning with exceptions. A declarative modeltheoretic semantics of DLP is provided, which is shown to generalize the answer set semantics of disjunctive logic programs. The knowledge modeling features of the language are illustrated by encoding classical nonmonotonic problems in DLP . The complexity of DLP is analyzed, proving that inheritance does not cause any computational overhead, as reasoning in DLP has exactly the same complexity as reasoning in disjunctive logic programming. This is conrmed by the existence of an ecient translation from DLP to plain disjunctive logic programming. Using this translation, an advanced KR system supporting the DLP language has been implemented on top of ...
Results 1  10
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350