opérateur de Bellman

CONT: The goal of a reinforcement learning (RL) agent is to optimize its policy to maximize the long-term return through repeated interaction with an external environment. The interaction is often modeled as a Markov decision process, whose value functions are the unique fixed points of their corresponding Bellman operators.