no code implementations • 29 Oct 2020 • Jakob J. Hollenstein, Sayantan Auddy, Matteo Saveriano, Erwan Renaudo, Justus Piater
Sufficient exploration is paramount for the success of a reinforcement learning agent.
no code implementations • 24 Oct 2020 • Jakob J. Hollenstein, Erwan Renaudo, Matteo Saveriano, Justus Piater
Local policy search is performed by most Deep Reinforcement Learning (D-RL) methods, which increases the risk of getting trapped in a local minimum.
Model-based Reinforcement Learning reinforcement-learning +1
no code implementations • 25 Sep 2019 • Jakob J. Hollenstein, Erwan Renaudo, Justus Piater
Most Deep Reinforcement Learning methods perform local search and therefore are prone to get stuck on non-optimal solutions.
Model-based Reinforcement Learning reinforcement-learning +1