Lehrinhalte
Review of machine learning background
Black box Reinforcement Learning
Modeling as bandit, Markov Decision Processes and Partially Observable Markov Decision Processes
Optimal control
System identification
Learning value functions
Policy search
Deep value functions methods
Deep policy search methods
Exploration vs exploitation
Hierarchical reinforcement learning
Intrinsic motivation
Voraussetzungen
Good programming in Python.
Lecture Statistical Machine Learning is helpful but not mandatory.
Review of machine learning background
Black box Reinforcement Learning
Modeling as bandit, Markov Decision Processes and Partially Observable Markov Decision Processes
Optimal control
System identification
Learning value functions
Policy search
Deep value functions methods
Deep policy search methods
Exploration vs exploitation
Hierarchical reinforcement learning
Intrinsic motivation
Voraussetzungen
Good programming in Python.
Lecture Statistical Machine Learning is helpful but not mandatory.
- Lehrende: Georgia Chalvatzaki
- Lehrende: Carlo D'Eramo
- Lehrende: Jan Peters
- Lehrende: Davide Tateo
Semester: Verão 2022