Neural Networks Made Easy (part 67): Using Past Experience To Solve New Tasks

Reinforcement learning is a method of maximizing rewards from interactions with the environment, but sometimes restrictions on interactions can make this difficult. Offline reinforcement learning allows for training on a limited archive of previous interactions, but can still face challenges in complex environments. The ExORL method is one solution to this issue, but using data from real interactions can also be effective.