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Practical Kernel-Based Reinforcement Learning
André M. S. Barreto, Doina Precup, Joelle Pineau
Kernel-based reinforcement learning (KBRL) stands out among reinforcement learning algorithms for its strong theoretical guarantees. By casting the learning problem as a local kern…
Representation as a Service
Ouais Alsharif, Philip Bachman, Joelle Pineau
Consider a Machine Learning Service Provider (MLSP) designed to rapidly create highly accurate learners for a never-ending stream of new tasks. The challenge is to produce task-spe…
Non-Deterministic Policies in Markovian Decision Processes
Mahdi Milani Fard, Joelle Pineau
Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision-making problem…
Online Planning Algorithms for POMDPs
Stéphane Ross, Joelle Pineau, Sébastien Paquet +1
Partially Observable Markov Decision Processes (POMDPs) provide a rich framework for sequential decision-making under uncertainty in stochastic domains. However, solving a POMDP is…