This self-contained book provides three fundamental and generic approaches (logical, probabilistic, and modal) to representing and reasoning with agent epistemic states, specifically in the context of decision making. Each of these approaches can be applied to the construction of intelligent software agents for making decisions, thereby creating computational foundations for decision-making agents. In addition, the book introduces a formal integration of the three approaches into a single unified approach that combines the advantages of all the approaches. Finally, the symbolic argumentation approach to decision making developed in this book, combining logic and probability, offers several advantages over the traditional approach to decision making which is based on simple rule-based expert systems or expected utility theory.Sample Chapter(s)Chapter 1: Modeling Agent Epistemic States: An Informal Overview (202 KB)Contents:Modeling Agent Epistemic States: An Informal OverviewMathematical PreliminariesClassical Logics for the Propositional Epistemic ModelLogic ProgrammingLogical Rules for Making DecisionsBayesian Belief NetworksInfluence Diagrams for Making DecisionsModal Logics for the Possible World Epistemic ModelSymbolic Argumentation for Decision MakingReadership: Undergraduates and graduates majoring in artificial intelligence, computer professionals and researchers from the decision science community.

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