In this third Part of Applying Temporal Difference Methods to Machine Learning, I will be experimenting with the intra-sequence update variant of TD learning. It is a method where after each time step, the parameters are updated rather than waiting at the end of the sequence. 1,075 more words
Tags » Reinforcement Learning
In this Part 2 of Applying Temporal Difference Methods to Machine Learning, I will show results of applying what Sutton refers to the traditional machine learning approach compared to the Temporal Difference approach. 974 more words
In this article, we are going to cover how to build an AI driving agent for a car.
You got a car, you know where to go using the GPS waypoints, the car has camera which can see the oncoming traffic and the traffic signal. 1,360 more words
In this post I detail my project for the course Reinforcement Learning (COMP767) taken at McGill, applying Temporal Difference (TD) methods in a Machine Learning setting. 1,263 more words