Model-based Bayesian reinforcement learning has generated significant interest in the AI community as it provides an elegant solution to the optimal exploration-exploitation trade...
Recent decision-theoric planning algorithms are able to find optimal solutions in large problems, using Factored Markov Decision Processes (fmdps). However, these algorithms need ...
Thomas Degris, Olivier Sigaud, Pierre-Henri Wuille...
Due to the unavoidable fact that a robot’s sensors will be limited in some manner, it is entirely possible that it can find itself unable to distinguish between differing state...
An explicit exploration strategy is necessary in reinforcement learning (RL) to balance the need to reduce the uncertainty associated with the expected outcome of an action and the...
World steel trade becomes more competitive every day and new high international quality standards and productivity levels can only be achieved by applying the latest computational...