MODEL-FREE CONTROL FOR REINFORCEMENT LEARNING AGENTS

• Main Authors: URIA-MARTINEZ, Benigno, BLUNDELL, Charles
• Format: Patent
• Language: English; French; German
• Published: 27.03.2024
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; PHYSICS

Methods, systems, and apparatus for selecting actions to be performed by an agent interacting with an environment. One method includes maintaining return data that maps each observation-action pair to a respective return, the action in each observation-action pair being an action that was performed by the agent in response to the observation in the observation-action pair and the respective return mapped to by each of the observation-action pairs being a return that resulted from the agent performing the action in the observation-action pair; receiving a current observation; determining whether the current observation matches any observation identified in the return data; and in response to determining that the current observation matches a first observation identified in the return data, selecting an action to be performed by the agent using the returns mapped to by observation-action pairs in the return data that include the first observation.