Multi-Agent Systems & Agentic AI Course
The course hub for a university-style class on multi-agent systems and agentic AI, holding lecture slides, code, tutorials, and reading materials covering reinforcement learning and multi-agent reinforcement learning.
This repository is the central hub for a course on multi-agent systems and agentic AI, covering how reinforcement learning drives intelligent decision-making in complex settings and the emerging area of agentic AI, combining core theory, recent research, and practical applications. It holds lecture slides and notes, code and tutorials, and reading materials, organized around two topics: agentic AI and reinforcement learning.
Listed resources include the Sutton and Barto reinforcement learning textbook, the Gymnasium and PettingZoo environment libraries, the TorchRL and StableBaselines3 training libraries, a multi-agent reinforcement learning textbook by Albrecht, Christianos, and Schafer, and the MARLLib and Mava multi-agent RL libraries.