Tags » Reinforcement Learning

Applying Temporal Difference Methods to Machine Learning — Part 3

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

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Applying Temporal Difference Methods to Machine Learning — Part 2

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

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DIY Autonomous Cars 101: Developing a Driving AI Agent

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

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Markov Decision processes

A tuple – (S,s1,A,P,R)

S – finite set of states.

s1 – initial state.

A – finite set of actions.

P – Given a state s1 and action a, what is the probability of ending up at a particular state s2? 264 more words

Artificial Intelligence

Applying Temporal Difference Methods to Machine Learning -- Part 1

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

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