Algorithm Design

Transitive RL: A Divide-and-Conquer Approach to Scalable Off-Policy Reinforcement Learning

This article introduces Transitive RL (TRL), a novel reinforcement learning algorithm that leverages a divide-and-conquer paradigm to address scalability issues in off-policy RL for long-horizon tasks.