In this paper, we propose to develop the supervised classification method Fuzzy Pattern Matching to be in addition a non supervised one. The goal is to monitor dynamic systems with...
In many practical reinforcement learning problems, the state space is too large to permit an exact representation of the value function, much less the time required to compute it. ...
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
er provides new techniques for abstracting the state space of a Markov Decision Process (MDP). These techniques extend one of the recent minimization models, known as -reduction, ...
— Reinforcement Learning (RL) provides a promising new approach to systems performance management that differs radically from standard queuing-theoretic approaches making use of ...
Gerald Tesauro, Nicholas K. Jong, Rajarshi Das, Mo...