This paper is about Reinforcement Learning (RL) applied to online parameter tuning in Stochastic Local Search (SLS) methods. In particular a novel application of RL is considered i...
The performance of a learning classifier system is due to its two main components. First, it evolves new structures by generating new rules in a genetic process; second, it adjust...
— 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...
Typical conversational recommender systems support interactive strategies that are hard-coded in advance and followed rigidly during a recommendation session. In fact, Reinforceme...
Gaussian Process Temporal Difference (GPTD) learning offers a Bayesian solution to the policy evaluation problem of reinforcement learning. In this paper we extend the GPTD framew...