Computational Game Theory


The aims of the course are:

  • To introduce the student to the notion of game, its various solution concepts, and other basic notions and tools of game theory, as well as the main application areas in which they apply;
  • To formalise the notion of strategic thinking and rational choice using the tools of game theory, and to provide insights into adopting game theory in modelling applications.
  • To establish the links between game theory, computer science and economics, with an emphasis on the computation aspects.
  • To introduce contemporary topics in the intersection of game theory, computer science and economics.

General characterization





Responsible teacher

João Alexandre Carvalho Pinheiro Leite


Weekly - 4

Total - 52

Teaching language



JAVA programming.


Yoav Shoham and Kevin Leyton-Brown , Essentials of Game Theory: A Concise Multidisciplinary Introduction, Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool Publishers, 2008.

Yoav Shoham and Kevin Leyton-Brown, Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations, Cambridge University Press, 2009.

Noam Nisan, Tim Roughgarden, Eva Tardos and Vijay V. Vazirani (Eds.), Algorithmic Game Theory, Cambridge University Press, 2007.

Teaching method

Available soon

Evaluation method


Practical/Summative Assessment Component

The practical assessment component consists of the evaluation, on a scale of 0-20 values, rounded to the first decimal case, obtained through the arithmetic average of the classification of 7 components:

  • answers to 4 small quizzes,
  • evaluation of the strategies used in 2 tournaments
  • the attendance of at least 8 lab or problem-solving classes (see plan in slides of 1st lecture) and active participation, dedication, and obtained results in the activities of those classes.

Important Dates (to be confirmed)


  • to be announced
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The dates may change, which will be communicated in a timely manner.

Theoretical Assessment Component

The Theoretical assessment component consists of the evaluation, on a scale of 0-20 values, rounded to the first decimal case, obtained through two tests or an exam.

Important Dates (to be confirmed)

Tests (closed book): 

  • to be announced
  • to be announced

Passing Criteria and Final Grade

A student is approved when cumulatively obtaining a grade equal to or greater than 9.5 in the Theoretical component and a grade equal to or greater than 9.5 in the weighted average of the theoretical (50%) and practical ( 50%) components.

The final grade is given by the weighted average of the theoretical (50%) and practical (50%) components, possibly incremented by a bonus (max 3 values) resulting from the final rankings in the tournaments, rounded up to the nearest integer.

Grade Improvement

The improvement of the grade is calculated as described above, and the student may choose to improve the theoretical component and/or the practical component (the latter only for students of previous editions), governed by the same rules and deadlines as the current edition. The final grade is calculated taking into account the theoretical and practical components.


The UNL Code of Ethics, the FCT Evaluation Regulation, as well as all orders that regulate this matter, will be applied scrupulously.

All the code used to answer the quiz and to participate in the tournaments must be original. Only the code made available or expressly authorized by the teachers can be reused. Namely, students will not be able to reuse code submitted in previous editions of this course, even if it was developed by them. Failure to comply with this rule constitutes plagiarism and is punished with failure in the course.

Subject matter

Game Theory

Utility Theory, Games in Normal-Form, Pareto optimality, Best response and Nash equilibrium, Mixed Strategies, Maxmin and Minmax, Correlated Equilibrium, Perfect-Information Extensive-Form Games, Subgame Perfection, Backward Induction, Imperfect-Information Extensive-Form Games, Perfect Recall, Repeated Games, Infinitely Repeated Games, Bayesian Games.

Mechanism Design

Social Choice, Voting, Voting Paradoxes, Arrow''s Theorem, Muller-Satterthwaite Theorem, Mechanisms with money, VCG mechanism, Auctions, Mechanisms without Money.


Programs where the course is taught: