 Additive state decomposition

Additive State Decomposition is a technique often used in control theory and reinforcement learning to break down complex systems or functions into simpler, more manageable components. The idea is to represent a state or a task as a sum of simpler states or tasks. This can help in understanding, analyzing, or solving problems by allowing for modularity and easier manipulation of different parts of the system.