Lectures Notes on Algorithmic Game Theory

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Lectures Notes on Algorithmic Game Theory Stanford CS364A, Fall 2013
Lecture #1: Introduction and Examples Lecture #2: Mechanism Design Basics Lecture #3: Myerson’s Lemma Lecture #4: Algorithmic Mechanism Design Lecture #5: Revenue-Maximizing Auctions Lecture #6: Simple Near-Optimal Auctions Lecture #7: Multi-Parameter Mechanism Design and the VCG Mechanism Lecture #8: Combinatorial and Wireless Spectrum Auctions Lecture #9: Beyond Quasi-Linearity Lecture #10: Kidney Exchange and Stable Matching Lecture #11: Selfish Routing and the Price of Anarchy Lecture #12: More on Selfish Routing Lecture #13: Potential Games; A Hierarchy of Equilibria Lecture #14: Robust Price-of-Anarchy Bounds in Smooth Games Lecture #15: Best-Case and Strong Nash Equilibria Lecture #16: Best-Response Dynamics Lecture #17: No-Regret Dynamics Lecture #18: From External Regret to Swap Regret and the Minimax Theorem Lecture #19: Pure Nash Equilibria and PLS-Completeness Lecture #20: Mixed Nash Equilibria and PPAD-Completeness

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关键词：Game Theory Algorithmic Algorithm Lectures Lecture

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