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YaBoiSmokey
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Reinforcement learning is a method utilized in artificial intelligence and machine learning to describe the learning process through interaction between an agent (system or algorithm) and an environment. In this method, the agent observes the states of the environment and takes actions based on these observations.
The key components of reinforcement learning are:
Agent: The system that takes actions in the environment and learns from the outcomes of these actions.
Environment: The world or system with which the agent interacts.
State: The current conditions and situations in the environment for the agent.
Policy: The strategy that determines which action the agent will take in a given state.
This method is applied in various areas such as games, robotics, automated systems, etc. For example, a robot learning to autonomously navigate an environment.
The key components of reinforcement learning are:
Agent: The system that takes actions in the environment and learns from the outcomes of these actions.
Environment: The world or system with which the agent interacts.
State: The current conditions and situations in the environment for the agent.
Policy: The strategy that determines which action the agent will take in a given state.
This method is applied in various areas such as games, robotics, automated systems, etc. For example, a robot learning to autonomously navigate an environment.