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| DESCRIPTION | This course provides a foundational introduction to microeconomics, game theory, and algorithmic mechanism design, with a specific focus on their application to modern multi-agent systems for AIoT. Students will explore how economic principles and strategic interactions govern the behavior of agents in a variety of networked environments, including adversarial defense, information systems, communication networks, social networks, and cyber-physical systems like energy and transportation grids. The curriculum bridges theoretical concepts with practical applications. Core topics include market mechanisms, consumer preferences, and the objectives of cost and welfare maximization. A significant portion of the course is dedicated to multi-agent game theory, covering strategic games, pure and mixed strategy Nash equilibrium, correlated equilibrium, and the dynamics of repeated games. We will also explore extensive-form games, solution concepts like backward induction and subgame perfect equilibrium, and games of incomplete information, such as Bayesian games. The course then advances to contemporary multi-agent paradigms, examining bandit and reinforcement learning algorithms for sequential decision-making under uncertainty, the principles of federated learning algorithms for privacy-preserving distributed optimization, and their connections to multi-agent mechanism design—including auctions, pricing, contracts, facility location, and information manipulation. The course concludes by tying these elements together within the context of distributed systems that underpin these multi-agent interactions. |
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| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6938) | We 09:00AM - 11:50AM | Rm 205, C7 Library | DUAN, Lingjie | 30 | 18 | 12 | 0 |