We present new algorithms for inverse optimal control (or inverse reinforcement learning, IRL) within the framework of linearlysolvable MDPs (LMDPs). Unlike most prior IRL algorit...
Abstract. Recent research in automated highway systems has ranged from low-level vision-based controllers to high-level route-guidance software. However, there is currently no syst...
Research in reinforcement learning has produced algorithms for optimal decision making under uncertainty that fall within two main types. The first employs a Bayesian framework, ...
In this paper, we present a novel method to adapt the temporal radio maps for indoor location determination by offsetting the variational environmental factors using data mining t...
Learning how to defeat human players is a challenging task in today's commercial computer games. This paper suggests a goal-directed hierarchical dynamic scripting approach f...