Bellman Equation Calculator

The Bellman equation is a fundamental component in reinforcement learning and dynamic programming. It recursively defines the value of a state as the immediate reward plus the discounted future value, factoring in the policy. The equation is typically expressed as:

\[ V(s) = R(s) + \gamma \sum_{s'} P(s'|s,a) V(s') \]

Where:

• \( V(s) \) is the value function at state \( s \).
• \( R(s) \) is the immediate reward.
• \( \gamma \) is the discount factor.
• \( \sum_{s'} P(s'|s,a) V(s') \) represents the expected value of the next state, considering the policy.

This calculator allows you to compute the value function based on these parameters, making it useful for studies in decision processes and reinforcement learning.