Mini toolsDefinition
A function that estimates the long-term cumulative reward an agent can expect to receive from a given state or state-action pair.
Detailed Explanation
Value functions estimate the expected cumulative discounted reward from following a particular policy from a given state (state-value function) or after taking a specific action in a state (action-value function). They are central to many reinforcement learning algorithms and help agents make decisions that maximize long-term reward.
Use Cases
Strategic planning in games, robot path planning, resource allocation, portfolio management
