Building upon the theoretical methods discussed in the lecture "Cognitive Computing: Reasoning and Decision Making under Uncertainty", this seminar provides further insight about practical methods and applications of sequential decision Making and Reinforcement Learning for assistive cooperative agents. In particular, we will learn how agents can use modern Bayesian inference about the mental states of other agents to support them in exploring and navigating unknown environments. The seminar will first take a closer look at the theoretical basis of the underlying inference and decision-making models and methods (for both the exploring and the assisting agent), before participants will have the chance to implement and test solutions in the second half of the semester.
Lecture "Reasoning and Decision Making unter Uncertainty"
Frequency | Weekday | Time | Format / Place | Period |
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Module | Course | Requirements | |
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39-Inf-KR Cognitive Computing / Kognitives Rechnen | Angewandtes Kognitives Rechnen | Student information | |
39-M-Inf-VKI Vertiefung Künstliche Intelligenz | Spezielle Themen der Künstlichen Intelligenz | Graded examination
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Student information |
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