核心概念
World models can effectively handle observation delays in partially observable environments, improving RL performance by up to 30%.
統計資料
"Experiments suggest that one of our methods can out-perform a naive model-based approach by up to %30."
引述
"In scenarios where timely decision-making is critical and agents cannot afford to wait for updated state observations, RL algorithms must nonetheless find effective control policies subject to delay constraints."
"World models have recently shown significant success in integrating past observations and learning the dynamics of the environment."
"Our methods exhibit greater resilience and one of them improves by approximately 30%."