Vrije Universiteit Brussel Faculteit Wetenschappen Vakgroep Informatica E J I R V S C I E N U T N I a V

In this dissertation we investigate logic programming to model decision-making. To this extent, we introduce three formalisms with increasing expressiveness. The most basic one, called choice logic programming, allows circumstance-dependent decisions. The stable models of the program correspond to the rational solutions of the represented decision-problem. To support dynamic preference-based decision-making, we extend our formalism to ordered choice logic programming. To accommodate the various ways two equally preferred alternatives are dealt with, both the skeptical stable model semantics and the more credulous answer set semantics are introduced. Decisions often have to be made without complete information. In order to deal with uncertainty, dynamically ordered probabilistic choice logic programs are presented. The stable models of these programs represent those solutions that deal with uncertainty in a rational manner. Game theory, a collection of analytical tools for studying the interaction of decision-makers, is used to demonstrate the effectiveness of our formalisms. Strategic games and extensive games with perfect information can be elegantly represented in our formalism such that the equilibria of the games can be retrieved as the stable models or answer sets of the programs. These equilibria are not player-deterministic in the sense that a single player, given the other players’ actions, could rationally leave an equilibrium state. We introduce player-deterministic, called cautious, Nash and subgame perfect equilibria as the skeptical stable models of the transformed game. To study the decision-process and the interaction between various decision-makers, we introduce a framework for logic programming agents. When applied to game theory, this enables us to monitor and reason about the knowledge and beliefs of each single player.