187 citations · 456 across the 29 of their papers we have counts for
3 papers · 2 filters
Safe Policy Improvement with Baseline Bootstrapping
Romain Laroche, Paul Trichelair, Rémi Tachet des Combes
This paper considers Safe Policy Improvement (SPI) in Batch Reinforcement Learning (Batch RL): from a fixed dataset and without direct access to the true environment, train a polic…
Hybrid Reward Architecture for Reinforcement Learning
Harm van Seijen, Mehdi Fatemi, Joshua Romoff +3
One of the main challenges in reinforcement learning (RL) is generalisation. In typical deep RL methods this is achieved by approximating the optimal value function with a low-dime…
Multi-Advisor Reinforcement Learning
Romain Laroche, Mehdi Fatemi, Joshua Romoff +1
We consider tackling a single-agent RL problem by distributing it to learners. These learners, called advisors, endeavour to solve the problem from a different focus. Their adv…