Adaptive Skill

Adaptive skill research focuses on developing systems capable of learning and applying diverse skills in dynamic environments, aiming to improve efficiency and robustness in tasks like navigation and reinforcement learning. Current approaches involve learning ensembles of low-level skills combined by high-level decision-making processes, often using reinforcement learning architectures with adaptive skill weighting or distribution mechanisms. This work is significant for advancing artificial intelligence by enabling agents to generalize better to unseen situations and efficiently explore complex environments, with potential applications in robotics, autonomous systems, and decision-making under uncertainty.