Implementation of SPIBB-DQN
This project can be used to reproduce the DQN implementation presented in the ICML2019 paper: Safe Policy Improvement with Baseline Bootstrapping, by Romain Laroche, Paul Trichelair, and Rémi Tachet des Combes. For the finite MDPs…
Implementation of Safe Policy Improvement with Baseline Bootstrapping
This project can be used to reproduce the finite MDPs experiments presented in the ICML2019 paper: Safe Policy Improvement with Baseline Bootstrapping, by Romain Laroche, Paul Trichelair, and Rémi Tachet des Combes. For the DQN…
Presentation at datafest, May 2019 in Moscow
The presentation starts with a brief introduction of Reinforcement Learning (RL) and an overview of its success. Even though these achievements are compelling, state-of-the-art algorithms require an unreasonable amount of data. Moreover, they sometimes converge…