inf5104 - Fundamentals of Game Theory in Energy Systems (Course overview)

inf5104 - Fundamentals of Game Theory in Energy Systems (Course overview)

Department of Computing Science 6 KP
Module components Semester courses Summer semester 2025 Examination
Lecture
  • Unlimited access 2.01.5104 - Game Theory in Energy Systems Show lecturers
    • Prof. Dr. Astrid Nieße

    The course times are not decided yet.
    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

Exercises
  • Unlimited access 2.01.5104 - Game Theory in Energy Systems Show lecturers
    • Prof. Dr. Astrid Nieße

    The course times are not decided yet.
    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

Notes on the module
Prerequisites

Useful prior knowledge: Fundamentals of optimization

Prüfungszeiten

Following the event period

Module examination

Written exam

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.