Distributed Multiagent Systems: Coordination and Learning

This lecture covers the fundamentals of distributed multiagent systems, focusing on coordination and learning mechanisms. Topics include social laws, task exchange in contract nets, distributed constraint satisfaction, and various coordination protocols. The instructor discusses decentralized, distributed, and centralized multi-agent architectures, as well as key concepts like no-regret learning, anti-coordination, equilibrium, and confidence bounds. Different algorithms for solving constraint satisfaction problems, such as backtracking, dynamic programming, and distributed local search, are explored in detail. The lecture also delves into practical examples and challenges in implementing these algorithms in real-world scenarios.