Temporal Difference Learning

It is a reinforcement learning method that updates value estimates using the difference between successive estimates. Instead of waiting for a final reward, the algorithm continuously adjusts its value estimates based on immediate feedback from the environment. This approach enables faster and more efficient learning in environments where rewards are sparse or delayed.

Sign up for the Newsletter
Thank you for subscribing to our newsletter!