Reinforcement Learning Algorithms with Python

Generalization

The concept of generalization refers to two aspects that are different, but somehow related. In general terms, the concept of generalization in reinforcement learning refers to the capability of an algorithm to obtain good performance in a related environment. For example, if an agent has been trained to walk on dirty roads, we might expect that the same agent will perform well on paved roads. The better the generalization capabilities, the better the agent will perform in different environments. The second and lesser-used means of generalization refers to the property of the algorithm to achieve good performance in an environment where only limited data can be gathered.

In RL, the agent can choose the states to visit by itself ...