Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
Planning as heuristic search is a powerful approach to solving domain independent planning problems. In recent years, various successful heuristics and planners like FF, LPG, FAST...
Martin Wehrle, Sebastian Kupferschmid, Andreas Pod...
We present a technique that provides progressive transmission and near-lossless compression in one single framework. The proposed technique produces a bitstream that results in pr...
The inference of evolutionary trees using approaches which attempt to solve the maximum parsimony (MP) and maximum likelihood (ML) optimization problems is a standard part of much...
Many real processes are composed of a n-fold repetition of some simpler process. If the whole process can be modelled with a neural network, we present a method to derive a model ...