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Harm H Van Seijen

2 accepted papers

2022

Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods

ICML 2022spotlight

In recent years, a growing number of deep model-based reinforcement learning (RL) methods have been introduced. The interest in deep model-based RL is not surprising, given its many potential benefits, such as higher sample efficiency and the potential for fast adaption to changes in the environment…

2021

Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks

ICML 2021spotlight

We propose the k-Shortest-Path (k-SP) constraint: a novel constraint on the agent’s trajectory that improves the sample efficiency in sparse-reward MDPs. We show that any optimal policy necessarily satisfies the k-SP constraint. Notably, the k-SP constraint prevents the policy from exploring state-a…