Table of Contents
Multi-Agent Systems is a fascinating and crucial field in modern artificial intelligence, with extensive applications and intersections with multiple disciplines. This course offers a systematic introduction to the field, equipping learners with in-depth knowledge and practical skills.
Course Objectives:
- Master the basic concepts of multi-agent systems.
- Master the common forms of games and game analysis methods.
- Master the common reinforcement learning and multi-agent reinforcement learning methods.
- Implement algorithms and apply them to practical problems.
Prerequisite Knowledge:
- Calculus, Linear Algebra, Probability Theory.
- Basics of Artificial Intelligence / Machine Learning (Supervised Learning).
- Python programming and the usage of related tools / libraries.
- Basic experience in GPU training.
Contact Info
- Instructor
- Yaodong Yang (yaodong.yang@pku.edu.cn)
- TAs
- Qinghao Wang (wqh@pku.edu.cn)
- Chengdong Ma (mcd1619@outlook.com)
- Yifan Zhong (zhongyifan@stu.pku.edu.cn)
- Zhaowei Zhang (zwzhang@stu.pku.edu.cn)
- Xiaoyuan Zhang (zhangxiaoyuan@bigai.ai)