Continuous space: action space

This lecture introduces the concept of continuous state and action spaces in reinforcement learning, focusing on methods to transfer techniques from discrete to continuous spaces. Topics covered include parametric approximation, SARSA algorithm, eligibility traces, and results from the mountain car task.