This information is indicative and can be subject to change.
Multi-agent systems
Teacher: Arianna Novaro
E-mail: [email protected]
ECTS: 2.5
Evaluation: Assignment(s) and final written exam.
Previsional Place and time: TBDMSE (3 hours/week between January and February)
Prerequisites: Basics of Game Theory and programming useful but not necessary.Mathematical maturity (understanding and writing mathematical models and proofs); familiarity with game theory and basic programming useful (but not necessary).
Aim of the course: The field of Multi-Agent Systems (MAS) studies the interactions of several autonomous agents. The agents can be human or artificial, and their interactions can be of a cooperative or competitive nature. The behavior of the agents may be influenced by the information available to them, their mutual relationships, as well as their individual goals and preferences. In this course, we will see how to represent in a formal way the interactions of the agents in different MAS settings, with a special focus on those relevant to Economics, and we will investigate the related algorithmic and computational issues for those settings.
Syllabus:
(The list of covered topics may be subject to change).
Multi-agent systems
Teacher: Arianna Novaro
E-mail: [email protected]
ECTS: 2.5
Evaluation: Assignment(s) and final written exam.
Previsional Place and time: TBDMSE (3 hours/week between January and February)
Prerequisites: Basics of Game Theory and programming useful but not necessary.Mathematical maturity (understanding and writing mathematical models and proofs); familiarity with game theory and basic programming useful (but not necessary).
Aim of the course: The field of Multi-Agent Systems (MAS) studies the interactions of several autonomous agents. The agents can be human or artificial, and their interactions can be of a cooperative or competitive nature. The behavior of the agents may be influenced by the information available to them, their mutual relationships, as well as their individual goals and preferences. In this course, we will see how to represent in a formal way the interactions of the agents in different MAS settings, with a special focus on those relevant to Economics, and we will investigate the related algorithmic and computational issues for those settings.
Syllabus:
(The list of covered topics may be subject to change).
- Voting theory;
- Matching markets;
- Auctions;
- Participatory budgeting;
- Artificial societies and simulations with NetLogo.
| mas2122_finalexam-4.pdf |
References:
- Y. Shoham and K. Leyton-Brown, 'Multiagent Systems. Algorithmic, Game-Theoretic, and Logical Foundations'. Cambridge University Press, 2009. (E-version available here http://www.masfoundations.org/download.html).
- F. Brandt, V. Conitzer, U. Endriss, J. Lang, and A. D. Procaccia (editors), ‘Handbook of Computational Social Choice’. Cambridge University Press, 2016. (E-version available here http://www.cambridge.org/download_file/951600).
- Additional resources will be made available during the course.
