2 papers
cs.LG2026
Scalable Option Learning in High-Throughput Environments
Mikael Henaff, Scott Fujimoto, Michael Matthews +1
Hierarchical reinforcement learning (RL) has the potential to enable effective decision-making over long timescales. Existing approaches, while promising, have yet to realize the b…
cs.LG2025
Multi-Agent Craftax: Benchmarking Open-Ended Multi-Agent Reinforcement Learning at the Hyperscale
Bassel Al Omari, Michael Matthews, Alexander Rutherford +1
Progress in multi-agent reinforcement learning (MARL) requires challenging benchmarks that assess the limits of current methods. However, existing benchmarks often target narrow sh…