Knowledge-Based Systems Group

This seminar will cover different approaches to robot control divided into two tracks: Behavior Synthesis (BS) and Transfer Learning in Reinforcement Learning (RL). The first track studies different approaches to generate behavior models for an agent. The second track investigates the state of the art in reinforcement learning to learn a policy to control the robots actions.

Contents

The course introduces techniques for knowledge representation and reasoning. The topics covered are:

• First-order logic
• Expressing knowledge
• Full clausal logic
• Horn logic
• Procedural representations
• Answer set programming
• Production systems
• Description logics
• Inheritance networks
• Defaults
• Action
• Planning
• Abductive explanations
• Expressiveness/tractability trade-offs

Course Dates

Literature

Ronald J. Brachman and Hector J. Levesque.
Knowledge Representation and Reasoning.
Morgan Kaufmann, 2004.

The proseminar will be on different (sub-)topics from artificial intelligence. We largely follow the lines of the well known textbook by Stuart Russell and Peter Norvig “Artificial Intelligence - A Modern Approach”.