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B.E Artificial Intelligence and Machine Learning Game Theory for Data Science Syllabus - Mumbai University 2026

This is the Fourth Year AI-ML syllabus under REV-2019 'C' Scheme, in force from the academic year 2023-24. The University has not yet published an NEP 2020 syllabus for this year of the degree, and this is the scheme its examinations are set on.

Game-Theory-for-Data-Science.pdf
Semester 7 · Fourth Year AI-ML

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Syllabus for Game Theory for Data Science

Semester 7 · Fourth Year AI-ML

Module 0: Prerequisite

  • Probability , Algebra

Module I: Introduction:

  • Making rational choices: basics of Games – strategy preferences – payoffs – Mathematical basics – Game theory Rational Choice – Basic solution concepts-non-cooperative versus cooperative games – Basic computational issues – finding equilibria and learning in gamesTypical application areas for game theory (e.g. Google’s sponsored search, eBay auctions, electricity trading markets).

Module II: Games with Perfect Information:

  • Strategic games – prisoner’s dilemma, matching pennies Nash equilibria – theory and illustrations – Cournot’s and Bertrand models of oligopoly – auctions – mixed strategy equilibrium – zero-sum games – Extensive Games with Perfect Information – repeated games (prisoner’s dilemma) subgame perfect Nash equilibrium; computational issues.

Module III: Games with Imperfect Information:

  • Games with Imperfect Information – Bayesian Games Motivational Examples – General Definitions – Information aspects – Illustrations – Extensive Games with Imperfect Information – Strategies – Nash Equilibrium – Beliefs and sequential equilibrium – Illustrations – Repeated Games The Prisoner’s Dilemma – Bargaining.

Module IV: Non-Cooperative Game Theory:

  • Non-cooperative Game Theory – Self-interested agents Games in normal form – Analyzing games: from optimality to equilibrium – Computing Solution Concepts of Normal Form Games – Computing Nash equilibria of two-player, zero-sum games –Computing Nash equilibria of two-player, generalsum games – Identifying dominated strategies

Module V: Mechanism Design Aggregating Preferences:

  • Social Choice – Formal Model – Voting – Existence of social functions – Ranking systems – Protocols for Strategic Agents: Mechanism Design – Mechanism design with unrestricted preferences – Efficient mechanisms – Vickrey and VCG mechanisms (shortest paths) – Combinatorial auctions – profit maximization Computational applications of mechanism design – applications in Computer Science Google’s sponsored search – eBay auctions – K-armed bandits.

Module VI: Repeated Games

  • Repeated games: The Prisoner’s Dilemma , The main idea , Preferences ,Infinitely repeated games, Strategies ,Some Nash equilibria of the infinitely repeated Prisoner’s Dilemma , Nash equilibrium payoffs of the infinitely repeated Prisoner’s Dilemma when the players are patient , Subgame perfect equilibria and the one-deviation property

Textbooks

  • 1 An Introduction to Game Theory by Martin J. Osborne
  • 2 M. J. Osborne, An Introduction to Game Theory. Oxford University Press, 2004
  • 1 M. Machler, E. Solan, S. Zamir, Game Theory, Cambridge University Press, 2013.
  • 2 N. Nisan, T. Roughgarden, E. Tardos, and V. V. Vazirani (Editors), Algorithmic Game Theory. Cambridge University Press, 2007.
  • 3 A.Dixit and S. Skeath, Games of Strategy, Second Edition. W W Norton & Co Inc, 2004.
  • 4 YoavShoham, Kevin Leyton-Brown, Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations, Cambridge University Press 2008.
  • 5 Zhu Han, DusitNiyato, WalidSaad, TamerBasar and Are Hjorungnes, “Game Theory in Wireless and Communication Networks”, Cambridge University Press, 2012.
  • 6 Y.Narahari, “Game Theory and Mechanism Design”, IISC Press, World Scientific. Digital References:
  • 1 https://nptel.ac.in/courses/110104063
  • 2 https://onlinecourses.nptel.ac.in/noc19_ge32/preview

Reproduced from the University of Mumbai syllabus for B.E. (Artificial Intelligence and Machine Learning) under REV-2019 'C' Scheme, in force from the academic year 2023-24. Wording is as printed in that syllabus. Module numbering is as printed there too.

The complete syllabus

This subject is cut from the University circular for its year. Open a document here if you want the whole thing rather than a single subject.

PDF 7.8 (R-A) B.E. (Artificial Intelligence and Machine Learning) Sem I & II (Revised, NEP 2020) NEP 2020 syllabus Read full PDF Read
PDF 6.21 (N) B.E. (Artificial Intelligence and Machine Learning) Sem III & IV (NEP 2020) NEP 2020 syllabus Read full PDF Read
PDF 6.42 (R) B.E. (Artificial Intelligence and Machine Learning) Third Year, Sem V & VI (REV-2019 'C' Scheme) REV-2019 'C' Scheme syllabus Read full PDF Read
PDF B.E. (Artificial Intelligence and Machine Learning) Fourth Year, Sem VII & VIII (REV-2019 'C' Scheme) REV-2019 'C' Scheme syllabus Read full PDF Read
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