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سرفصل های درس DAI در برخی از دیگر دانشگاه ها

سرفصل های درس DAI در برخی از دیگر دانشگاه ها. استاد درس: دکتر عبداله زاده درس: هوش مصنوعی توزیع شده ارائه کننده: مریم باحجب ایمانی. Stanford University. Modal logics of knowledge and belief logics of belief change multi-agent probability systems

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سرفصل های درس DAI در برخی از دیگر دانشگاه ها

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  1. سرفصل های درس DAI در برخی از دیگر دانشگاه ها استاد درس: دکتر عبداله زاده درس: هوش مصنوعی توزیع شده ارائه کننده: مریم باحجب ایمانی

  2. Stanford University • 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. • http://www.stanford.edu/class/cs224m/generalinfo.html هوش مصنوعی توزیع شده

  3. Harvard University • 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. • http://www.eecs.harvard.edu/cs285/index.html هوش مصنوعی توزیع شده

  4. Waterloo University • 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 • http://www.cs.uwaterloo.ca/~klarson/teaching/F08-886/ هوش مصنوعی توزیع شده

  5. University of Calgary • 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. • http://pages.cpsc.ucalgary.ca/~denzinge/courses/cs567-winter2011.html هوش مصنوعی توزیع شده

  6. University of Liverpool • 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 (egAgentO), agents as reactive systems (egsubsumption architecture); hybrid agents (eg PRS); layered agents (egInterrap) 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. • http://www.csc.liv.ac.uk/teaching/modules/year3s2/full-comp310.html هوش مصنوعی توزیع شده

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