Reasoning about perception of depth and about spatial relations between moving physical objects is a challenging problem. We investigate the representation of depth and motion by m...
Inverse Reinforcement Learning (IRL) is the problem of learning the reward function underlying a Markov Decision Process given the dynamics of the system and the behaviour of an e...
The paper presents the theoretical foundations and an algorithm to reduce the efforts of testing physical systems. A test is formally described as a set of stimuli (inputs to the ...
Agent-based modeling is a framework that allows the analysis of distributed command-by-influence using mission-type orders known for over a century as Auftragstaktik in German Arm...
Behavioural cloning is a method by which a machine learns control skills through observing what a human controller would do in a certain set of circumstances. More specifically, t...