استاد درس : دکتر عبداله زاده درس : هوش مصنوعی توزیع شده ارائه کننده : مریم باحجب ایمانی

 Modal logics of knowledge and belief  logics of belief change  multi-agent probability systems  introduction to non-cooperative game theory, mechanism design and auctions, cooperative and non- cooperative communication, and multi-agent learning.  Emphasis is on representation techniques and algorithms, drawn primarily from two disciplines - computer science (and, through it, philosophy) and game theory.  هوش مصنوعی توزیع شده 2

 Definitions and links to game theory, Stable matching, Contrasting ABT and AWT.  Game theory - examples: risk aversion, coordination failure, government subsidies.  Game theory - common knowledge, risk dominance, introduction to evolutionary game theory, forward induction.  Game theory, behavioral economics.  Social choice, evolutionary game theory, other MAS.  Social choice, complexity and mechanism design.  Prediction markets.  هوش مصنوعی توزیع شده 3

 Games (normal-form, extensive-form, repeated, stochastic, Bayesian)  Computation of game theoretic solution concepts  Bounded rationality  Social choice  Mechanism design  Auctions (single item, combinatorial, sponsored search)  Teams and coalitions  Multiagent learning  Applications  886/ 886/ هوش مصنوعی توزیع شده 4

 Modeling of agents  properties of multi-agent systems  communication between agents  interaction and cooperation concepts  forming and maintaining organizations  competitive agent environments  learning in multi-agent systems example systems.  winter2011.html winter2011.html هوش مصنوعی توزیع شده 5

 Introduction: what is an agent?: agents and objects; agents and expert systems; agents and distributed systems; typical application areas for agent systems.  IntelligentAgents: the design of intelligent agents - reasoning agents (eg AgentO), agents as reactive systems (eg subsumption architecture); hybrid agents (eg PRS); layered agents (eg Interrap) a contemporary (Java-based) framework for programming agents (eg the Jack language, the JAM! system).  Multi-Agent Systems: Classifying multi-agent interactions - cooperative versus non-cooperative; zero-sum and other interactions; what is cooperation? how cooperation occurs - the Prisoner's dilema and Axelrod's experiments; Interactions between self-interested agents: auctions & voting systems: negotiation; Interactions between benevolent agents: cooperative distributed problem solving (CDPS), partial global planning; coherence and coordination; Interaction languages and protocols: speech acts, KQML/KIF, the FIPA framework.  Advanced topics: One issue selected from the contemporary research literature, perhaps by guest lecturer.  هوش مصنوعی توزیع شده 6