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September 25, 2023

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Description

Algorithmic Game Theory. Instructor: Prof. Palash Dey, Department of Computer Science and Engineering, IIT Kharagpur.

Game theory is the formal study of interaction between self-interested (or goal-oriented) systems (or agents or decision makers or players), and strategic scenarios that arise in such settings. It began life in Economics in the 1940's with the work of von Neumann and Morgenstern, but has since been applied to an extraordinary range of subjects, including political science, evolutionary biology and even to inspection regimes for arms control. Game theory has for years also played an important, if less recognized, role in several branches of computer science. Applications within computer science include the use of games in automated verification and model checking to model computing systems in an unknown and possibly adverse environment. In AI games are applied to the analysis of multi-agent systems. Recently, with the advent of the internet and e-commerce, many game theoretic questions in the interplay between economics and computing have received extensive attention. These include electronic auctions, and more generally mechanism design questions (inverse game theory) related to finding incentive structures for cooperation between independent entities on the internet. Wherever game theory plays a quantitative role, algorithmic and computational questions related to solving games are also of central importance. This course discusses algorithmic aspects of game-theoretic models, with a focus on recent algorithmic and mathematical developments. (from nptel.ac.in)

Course Curriculum

  • Lecture 01 – Introduction to Computer Graphics Unlimited
  • Lecture 02 – Assumptions of Game Theory Unlimited
  • Lecture 03 – Examples of Games Unlimited
  • Lecture 04 – Equilibrium Concepts Unlimited
  • Lecture 05 – Nash Equilibrium Unlimited
  • Lecture 06 – Indifference Principle Unlimited
  • Lecture 07 – Security of Players Unlimited
  • Lecture 08 – Minmax Theorem Unlimited
  • Lecture 09 – Implications of Minmax Theorem Unlimited
  • Lecture 10 – MSNEs of Matrix Games Unlimited
  • Lecture 11 – Iterative Eliminations of Dominated Strategies Unlimited
  • Lecture 12 – Iterative Eliminations of Dominated Strategies (cont.) Unlimited
  • Lecture 13 – Braess’s Paradox Unlimited
  • Lecture 14 – Yao’s Lemma and its Applications Unlimited
  • Lecture 15 – Support Enumeration Algorithm Unlimited
  • Lecture 16 – Succinct Game Unlimited
  • Lecture 17 – Potential Games Unlimited
  • Lecture 18 – Best Response Dynamics Unlimited
  • Lecture 19 – Fast Convergence of Best Response Dynamics Unlimited
  • Lecture 20 – Computing ε-PSNE for Network Congestion Games Unlimited
  • Lecture 21 – PSNE for Congestion Games Unlimited
  • Lecture 23 – Functional NP Unlimited
  • Lecture 24 – PPAD Class Unlimited
  • Lecture 25 – Sperner’s Lemma Unlimited
  • Lecture 26 – Approximate MSNE Computation Unlimited
  • Lecture 27 – Correlated Equilibrium Unlimited
  • Lecture 28 – Coarse Correlated Equilibrium Unlimited
  • Lecture 29 – External Regret Framework Unlimited
  • Lecture 30 – Multiplicative Weight Algorithm Unlimited
  • Lecture 31 – Multiplicative Weight Algorithm (cont.) Unlimited
  • Lecture 32 – Swap Regret and Correlated Equilibrium Unlimited
  • Lecture 33 – Swap Regret to External Regret Reduction Unlimited
  • Lecture 34 – Braess’s Paradox and Pigou’s Network Unlimited
  • Lecture 35 – PoA of Selfish Routing Game Unlimited
  • Lecture 36 – PoA of Selfish Load Balancing Game Unlimited
  • Lecture 37 – Bayesian Game Unlimited
  • Lecture 38 – BNE of First Price Auction Unlimited
  • Lecture 39 – Extensive Form Game Unlimited
  • Lecture 40 – Mechanism Design Intro Unlimited
  • Lecture 41 – Implementation of Social Choice Functions Unlimited
  • Lecture 42 – Revelation Principle Unlimited
  • Lecture 43 – Properties of Social Choice Function Unlimited
  • Lecture 44 – Gibbard-Satterthwaite Theorem Unlimited
  • Lecture 45 – Quasilinear Environment Unlimited
  • Lecture 46 – Ex-Post Efficiency Unlimited
  • Lecture 47 – VCG Mechanism Unlimited
  • Lecture 48 – Example of VCG Mechanism Unlimited
  • Lecture 49 – Weighted VCG Unlimited
  • Lecture 50 – Affine Maximizer Unlimited
  • Lecture 51 – Recap of Topics Discussed So Far Unlimited
  • Lecture 52 – Single Parameter Domain Unlimited
  • Lecture 53 – DSIC in Single Parameter Domain Unlimited
  • Lecture 54 – Mayerson’s Lemma Unlimited
  • Lecture 55 – Sponsored Search Auction Unlimited
  • Lecture 56 – Intermediate Domain Unlimited
  • Lecture 57 – Algorithmic Mechanism Design Unlimited
  • Lecture 58 – Stable Matching Unlimited
  • Lecture 59 – Gale-Shapley Algorithm Unlimited
  • Lecture 60 – Properties of Stable Matching Unlimited

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