Method and system for implementing reinforcement learning agent using reinforcement learning processor

Abstract

The embodiments herein disclose a system and method for implementing reinforcement learning agents using a reinforcement learning processor. An application-domain specific instruction set (ASI) for implementing reinforcement learning agents and reward functions is created. Further, instructions are created by including at least one of the reinforcement learning agent ID vectors, the reinforcement learning environment ID vectors, and length of vector as an operand. The reinforcement learning agent ID vectors and the reinforcement learning environment ID vectors are pointers to a base address of an operations memory. Further, at least one of said reinforcement learning agent ID vector and reinforcement learning environment ID vector is embedded into operations associated with the decoded instruction. The instructions retrieved by agent ID vector indexed operation are executed using a second processor, and applied onto a group of reinforcement learning agents. The operations defined by the instructions are stored in an operations storage memory.