This seminar will cover different approaches to synthesize models for agent behavior, divided into two tracks: The first track focuses on creating behavior models using Learning-from-Demonstration and Behavior Trees. The second track investigates approaches from the field of Neurosymbolic AI to synthesize domain- and action models.
Contents This course is about the logic of knowledge bases, in two distinct but related senses. On the one hand, a knowledge base is a collection of sentences in a representation language that entails a certain picture of the world represented.
Contents Introduction to Mobile Robotics Basics of Probability Theory State Estimation Mapping Markov Localization Monte Carlo Localization Simultaneous Localization and Mapping (SLAM) Markov Decision Processes (MDPs) Partially observable Markov Decision Processes (POMDPs) Reasoning about action under uncertainty Course Dates The lecture starts on Friday, April 21, 2023.
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”.