Google AI’s New Study Enhance ReinforcementLearning Agent’s Generalization In Unseen Tasks

Reinforcement learning (RL) is a field of machine learning (ML) that involves training ML models to make a sequence of intelligent decisions to complete a task (such as robotic locomotion, playing video games, and more) in an uncertain, potentially complex environment.

RL agents have shown promising results in various complex tasks. However, it is challenging to transfer the agents’ capabilities to new tasks even when they are semantically equivalent. Consider a jumping task in which an agent, learning from image observations, must jump over an obstacle. Deep RL agents who have been taught a handful of these tasks with varied obstacle positions find it difficult to jump over obstacles in previously unknown locations.

https://www.marktechpost.com/2021/09/30/google-ais-new-study-enhance-reinforcement-learning-rl-agents-generalization-in-unseen-tasks-using-contrastive-behavioral-similarity-embeddings/