Reinforcement Learning
Environment
In RL, the world the agent interacts with, providing states, accepting actions, and returning rewards.
Related Concepts
- Agent: Explore how Agent relates to Environment
- State: Explore how State relates to Environment
- Reward: Explore how Reward relates to Environment
- Reinforcement Learning: Explore how Reinforcement Learning relates to Environment
Why It Matters
Understanding Environment is crucial for anyone working with reinforcement learning. This concept helps build a foundation for more advanced topics in AI and machine learning.
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This term is part of the comprehensive AI/ML glossary. Explore related terms to deepen your understanding of this interconnected field.
Tags
reinforcement-learning agent state reward
Related Terms
Agent
In RL, the learner or decision-maker that takes actions in an environment to maximize cumulative reward.
Reinforcement Learning
Learning through interaction with an environment, receiving rewards or penalties to learn optimal behavior policies.
Reward
A scalar feedback signal indicating how good an action was, used to train reinforcement learning agents.