DRL Taxonomy

Temporal-Difference Learning II and DRL Taxonomy

AI, ML
AI, ML, Reinforcement Learning, Temporal-Difference Learning, DRL Taxonomy

Temporal-Difference Learning II and DRL Taxonomy #

One-step TD methods bootstrap after a single transition. Multi-step methods instead use several observed rewards before bootstrapping, forming a bridge between TD(0) and Monte Carlo learning.

Course Content covered in this module:

  • Temporal-Difference Learning: n-step returns and TD(λ)
  • Classification of Reinforcement Learning approaches, algorithms and applications:
    • Model-Based versus Model-Free
    • Value-Based versus Policy-Based
    • On-Policy versus Off-Policy
The number of sampled steps controls how far learning looks ahead before it bootstraps.

Learning Objectives #

By the end of this module, you should be able to: