Value Function
In Data Science and Artificial Intelligence, a value function is a mathematical function that assigns a value to every possible state of an environment. It is used in reinforcement learning to determine the optimal action to take in a given state. The value of a state is defined as the expected cumulative reward that can be obtained from that state onwards. The value function can be estimated using various algorithms such as Monte Carlo, Temporal Difference, and Q-learning. It is an essential component of many reinforcement learning algorithms and is used to guide the agent towards the optimal policy.
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