Continuous Action Spaces
Continuous action spaces refer to a type of action space in reinforcement learning where the agent can take any action within a continuous range of values. This is in contrast to discrete action spaces, where the agent can only choose from a finite set of actions. Continuous action spaces are commonly used in robotics and control problems, where the agent needs to make precise and continuous movements. In order to solve problems with continuous action spaces, algorithms such as actor-critic methods and deep reinforcement learning are often used.
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