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B.E. (Artificial Intelligence and Data Science) Game Theory for Data Science Syllabus - Mumbai University

This is the Fourth Year BE AI and DS syllabus under CBCS REV-2019 'C' Scheme, in force from the academic year 2023-24. The University has published no NEP 2020 syllabus for Semesters V to VIII of any engineering branch, so this is the scheme you are examined on — exam form 1T01817 and 1T01818. The first and second years of the degree are on NEP 2020.

Game Theory for Data Science.pdf
Semester 7 · Fourth Year BE AI and DS · 3 credits · CBCS REV-2019 'C' Scheme

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Syllabus for Game Theory for Data Science

Semester 7 · Fourth Year BE AI and DS · 3 credits · CBCS REV-2019 'C' Scheme

Module Prerequisite 1 hours

  • Prerequisite Probability , Algebra
  • 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).
  • 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.
  • 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.
  • 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
  • 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.
  • 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

Text Books

  • 1 An Introduction to Game Theory by Martin J. Osborne
  • 2 M. J. Osborne, An Introduction to Game Theory. Oxford University Press, 2004

References

  • 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 Material

  • 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 Data Science), item 6.12 (N), under CBCS REV-2019 'C' Scheme, in force from the academic year 2023-24. Wording, module numbering and hours are as printed in that syllabus.

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.

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