Game Theory and Decision Theory in Agent-Based Systems

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This is a collection of papers from international researchers, that offers a broad view of the many ways game theory and decision theory can be applied in agent-based systems, from standard applications of the core elements of the theory to more cutting-edge developments. The range of topics discussed in this book should provide the reader with a comprehensive volume that reflects both the depth and breadth of work in applying techniques from game theory and decision theory to design agent-based systems. Chapters include: selecting partners; evolution of agents with moral sentiments in an IPD exercise; dynamic desires; emotions and personality; decision-theoretic approach to game theory; shopbot economics; finding the best way to join in; shopbots and pricebots in electronic service markets; polynomial time mechanisms; multi-agent Q-learning and regression trees; satisficing equilibria; investigating commitment flexibility in multi-agent contracts; pricing in agent economies using multi-agent Q-learning; using hypergames to increase planned payoff and reduce risk; bilateral negotiation with incomplete and uncertain information; and robust combinatorial auction protocol against false-name bids.