TDM: From Model-Free to Model-Based Deep Reinforcement Learning
Table of Contents
While simple, this thought experiment highlights some important aspects of human intelligence. For some tasks, we use a trial-and-error approach, and for others we use a planning approach. A similar phenomena seems to have emerged in reinforcement learning (RL).
In the parlance of RL, empirical results show that some tasks are better suited for model-free (trial-and-error) approaches, and others are better suited for model-based (planning) approaches.
Source: berkeley.edu
