Covers the characteristics, applications, and challenges of intelligent agents in software systems, emphasizing their role in making autonomous decisions and coordinating with other agents.
Explores applications of autonomous agents in UAVs, air traffic management, and logistics, focusing on MAS interactions and adaptive transportation networks.
Introduces reinforcement learning, covering its definitions, applications, and theoretical foundations, while outlining the course structure and objectives.
Explores coordination and learning in distributed multiagent systems, covering social laws, task exchange, constraint satisfaction, and coordination algorithms.
