environment
In reinforcement learning, the world that contains the agent and allows the agent to observe that world's state.
Plain English Explanation
In reinforcement learning, the world that contains the agent and allows the agent to observe that world's state. For example, the represented world can be a game like chess, or a physical world like a maze. When the agent applies an action to the environment, then the environment transitions between states.
How is it used?
Practitioners refer to environment when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.