inf5104 - Fundamentals of Game Theory in Energy Systems (Complete module description)

Module label	Fundamentals of Game Theory in Energy Systems
Module code	inf5104
Credit points	6.0 KP
Workload	180 h
Institute directory	Department of Computing Science
Applicability of the module	Master's Programme Computing Science (Master) > Angewandte Informatik Master's programme Digitalised Energy Systems (Master) > Computer Science and Energy Informatics
Responsible persons	Nieße, Astrid (module responsibility) Lehrenden, Die im Modul (authorised to take exams)
Prerequisites	Useful prior knowledge: Fundamentals of optimization
Skills to be acquired in this module	Upon successful completion of the course, students can understand fundamental concepts of game theory, and the relevance of these concepts to applications in energy informatics research. Professional competence The students: will be able to follow game-theoretic work in the application area of energy systems, and thus be able to reflect on the current state of research in this area Methological competence The students: can classify and formalise games and apply solution concepts for the presented types of games. Application examples can be examined for game types and the necessary simplifications can be evaluated. Social competence The students: create solutions in small teams present and discuss their solutions reflect the solutions of others in a constructive manner Self competence The students: derive connections between everyday situations and their game theory conceptualization.
Module contents	In this module, theoretical concepts from game theory are prepared and presented with connections to the application in cyber-physical energy systems (CPES). Fundamental concepts are discussed using easy-to-follow examples. These are: Game theory and decision theory Interdependencies Cooperative and non-cooperative game theory Utility, discrete and continuous strategy, dominant strategy Axioms of game theory Theorems of game theory Solution concepts for games, e.g. iterated elimination, backward induction Multi-step and repeated games Partial game perfection Discont factor Mechanims design, markets and auctions In CPES-application examples, references are made to distributed artificial intelligence and multi-agent systems, strategy learning, and operating in markets in energy applications
Recommended reading	Dario Bauso: Game Theory with Engineering Applications. Society for Indstrial and Applied Mathematics, Philadelphia, 2016 Shoham, Leyton-Brown: Multiagent systems. Cambridge University Press, 2010. http://www.masfoundations.org Fudenberg, Tirole: Game Theory. MIT Press, 1991
Links
Language of instruction	English
Duration (semesters)	1 Semester
Module frequency	every summer term
Module capacity	unlimited
Teaching/Learning method	V+Ü

Type of course	SWS	Frequency	Workload of compulsory attendance
Lecture	2	SuSe	28
Exercises	2	SuSe	28
Total module attendance time			56 h

Examination	Prüfungszeiten	Type of examination
Final exam of module	Following the event period	Written exam