Collaborative Research: III: Small: Closing Sim-to-Real Gap in Reinforcement Learning via Randomization, Alignment, and Derivation

Reinforcement Learning (RL) is a machine learning paradigm that strives to make optimal decision-making based on experience acting in an environment. In many cases, the "environment" refers to a simulator in the training stage and refers to the real world in the deployment stage. Training in the simulator brings a lot of advantages: lower cost,…