151818934 MULTI-AGENT SYSTEMS ( 3 Crd.Hrs )

This course introduces student’s systems with multiple agents that mutually cooperate together in order to perform joint task in order to improve system performance. The course will cover theory for strategic interaction between self-interested agents as well as more altruistic agents working explicitly together in complex distributed environments. Game theory and swarm intelligence will be central parts of the course curriculum. Students will be introduced to the techniques for developing autonomous agents in multi-agent systems. Emphasis on feedback optimization in multiagent reinforcement learning and cooperative coevolutionary algorithms. Mean topics covered in this course are mainly; Autonomous agents, reinforcement learning, evolutionary algorithms, reward shaping, evolutionary game theory, and swarm optimization. Course Objectives The major objectives of this course are to introduce students to the terms of 'agency' and ‘multi-agent system’ and how it is associated with developing intelligent software and the problems associated with designing multi-agent systems, as well as to introduce the decision making frameworks in multi-agent systems.