65 citations · 89 across the 17 of their papers we have counts for
4 papers · 1 filter
Test-Time Graph Search for Goal-Conditioned Reinforcement Learning
Evgenii Opryshko, Junwei Quan, Claas Voelcker +2
Offline goal-conditioned reinforcement learning (GCRL) often struggles with long-horizon tasks, where errors in value estimation accumulate and produce unreliable policies. It is t…
Relative Entropy Pathwise Policy Optimization
Claas Voelcker, Axel Brunnbauer, Marcel Hussing +6
Score-function based methods for policy learning, such as REINFORCE and PPO, have delivered strong results in game-playing and robotics, yet their high variance often undermines tr…
Calibrated Value-Aware Model Learning with Probabilistic Environment Models
Claas Voelcker, Anastasiia Pedan, Arash Ahmadian +3
The idea of value-aware model learning, that models should produce accurate value estimates, has gained prominence in model-based reinforcement learning. The MuZero loss, which pen…
Sorrel: A simple and flexible framework for multi-agent reinforcement learning
Rebekah A. Gelpí, Yibing Ju, Ethan C. Jackson +4
We introduce Sorrel (https://github.com/social-ai-uoft/sorrel), a simple Python interface for generating and testing new multi-agent reinforcement learning environments. This inter…