Reinforcement Learning Algorithms with Python

Transfer learning

Transferring knowledge between two environments, especially if these environments are similar to each other, is a hard task. Transfer learning strategies propose to bridge the knowledge gap so that the transition from an initial environment to a new one is as easy and smooth as possible. Specifically, transfer learning is the task of efficiently transferring knowledge from a source environment (or multiple environments) to a target environment. Thus, the more experience that has been acquired from a set of source tasks and transferred to a new target task, the faster the agent will learn and the better it will perform on the target task.

Generally speaking, when you think about an agent that hasn't been trained yet, you ...