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 2024 Examination
Lecture
• 2.01.5104 - Game Theory in Energy Systems
• Prof. Dr. Astrid Nieße

Dates on Monday, 29.07.2024 - Friday, 02.08.2024, Monday, 05.08.2024 - Friday, 09.08.2024 08:00 - 18:00
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
• 2.01.5104 - Game Theory in Energy Systems
• Prof. Dr. Astrid Nieße

Dates on Monday, 29.07.2024 - Friday, 02.08.2024, Monday, 05.08.2024 - Friday, 09.08.2024 08:00 - 18:00
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

Hinweise zum Modul
 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 competenceThe 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 areaMethological competenceThe 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 competenceThe students:create solutions in small teamspresent and discuss their solutionsreflect the solutions of others in a constructive mannerSelf competenceThe students:derive connections between everyday situations and their game theory conceptualization.