The independent choice logic for modelling multiple agents under uncertainty
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It is argued that the ICL provides a natural and concise representation for multi-agent decision-making under uncertainty that allows for the representation of structured probability tables, the dynamic construction of networks and a way to handle uncertainty and decisions in a logical representation.About:
This article is published in Artificial Intelligence.The article was published on 1997-07-15 and is currently open access. It has received 428 citations till now. The article focuses on the topics: Logic programming & Markov decision process.read more
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博弈论 : 矛盾冲突分析 = Game theory : analysis of conflict
Roger B. Myerson,剣平 費 +1 more
TL;DR: This chapter discusses Decision-Theoretic Foundations, Game Theory, Rationality, and Intelligence, and the Decision-Analytic Approach to Games, which aims to clarify the role of rationality in decision-making.
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Stochastic dynamic programming with factored representations
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Multi-agent influence diagrams for representing and solving games
Daphne Koller,Brian Milch +1 more
TL;DR: This paper provides a sound and complete graphical criterion for determining strategic relevance, and shows how strategic relevance can be used to detect structure in games, allowing a large game to be broken up into a set of interacting smaller games, which can be solved in sequence.
References
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Theory of Games and Economic Behavior
TL;DR: Theory of games and economic behavior as mentioned in this paper is the classic work upon which modern-day game theory is based, and it has been widely used to analyze a host of real-world phenomena from arms races to optimal policy choices of presidential candidates, from vaccination policy to major league baseball salary negotiations.
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Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference
TL;DR: Probabilistic Reasoning in Intelligent Systems as mentioned in this paper is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty, and provides a coherent explication of probability as a language for reasoning with partial belief.
Book
Markov Decision Processes: Discrete Stochastic Dynamic Programming
TL;DR: Puterman as discussed by the authors provides a uniquely up-to-date, unified, and rigorous treatment of the theoretical, computational, and applied research on Markov decision process models, focusing primarily on infinite horizon discrete time models and models with discrete time spaces while also examining models with arbitrary state spaces, finite horizon models, and continuous time discrete state models.
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A robust layered control system for a mobile robot
TL;DR: A new architecture for controlling mobile robots is described, building a robust and flexible robot control system that has been used to control a mobile robot wandering around unconstrained laboratory areas and computer machine rooms.
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A robust layered control system for a mobile robot
TL;DR: In this paper, a new architecture for controlling mobile robots is described, which is made up of asynchronous modules that communicate over low-bandwidth channels, each module is an instance of a fairly simple computational machine.