ARLBench: Flexible and Efficient Benchmarking for Hyperparameter Optimization in Reinforcement Learning
TL;DR: AUsing offline goal-conditioned RL to isolate the effects of exploration and objective design, this study shows that hyperparameter landscapes can be ...
TL;DR: From integrating RL with VLMs and LLMs to hyperparameter tuning, environment design, and generalization, 2024 was packed with innovation. We’ve highl...
TL;DR: A new contextual world-model that helps to generalize better to new scenarios by understanding contextual factors like robot mass or strength. This co...