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FEP3301 Computational Game Theory 8.0 credits

The course focuses on areas of game theory that appear to be most relevant for engineering applications. The emphasis is both on theoretical principles and on the application of the theory to problem formulation and problem solving. The course covers a wide range of topics, from different models of non-cooperative games and related equilibrium concepts, to cooperative games. The course also covers topics in mechanism design.

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Headings with content from the Course syllabus FEP3301 (Spring 2019–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

Strategic games in normal form, Kakutani’s fixed point theorem, best reply, Nash equilibrium, dominance solvability, rationalizability, existence of equilibria, zeros-sum games, minimax theorem, cardinality of solutions, refinement of Nash equilibria, robustness of equilibria, Bayesian games, potential games, submodular games, extensive games with perfect information, subgame perfect equilibria, repeated games and folk theorems, stochastic games, Markov perfect equilibria, finite and infinite evolutionary games, replicator dynamic, evolutionary stable states and sets, coalition games, core, kernel, nucleolus, Shapley value, social choice theory, Arrow’s impossibility theorem, implementation in dominant strategies, strategyproof implementation, Gibbard-Sattertwhwaite theorem, implementation with money, Groves mechanism, Clarke’s pivot rule, VCG mechanism, implementation in Nash equilibrium.

Intended learning outcomes

Upon completion of the course, the student should be able to:

-          formalize problems that involve more than one decision making entity in a game theoretical context

-          critically assess the research literature in the area

-          use the game theoretical tools and methods to solve problems

-          contribute to the research frontier in the area

Course disposition

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Literature and preparations

Specific prerequisites

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Recommended prerequisites

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Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

P, F


  • EXA1 - Examination, 8.0 credits, grading scale: P, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Other requirements for final grade

15 min oral presentation at one of the lectures

75% on weekly home-work problems and the presentation

50% on 72 h take home exam

Opportunity to complete the requirements via supplementary examination

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Opportunity to raise an approved grade via renewed examination

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Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course web

Further information about the course can be found on the Course web at the link below. Information on the Course web will later be moved to this site.

Course web FEP3301

Offered by

Main field of study

This course does not belong to any Main field of study.

Education cycle

Third cycle

Add-on studies

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György Dán (

Postgraduate course

Postgraduate courses at EECS/Network and Systems Engineering