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Q-Learning
Welcome to my column on reinforcement learning, where I spend some time going over some very interesting concepts revolving around the nature of learning with a computational approach. As with most…
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Q-Learning
Q-learning is one of the most popular Reinforcement learning algorithms and lends itself much more readily for learning through implementation of toy problems as opposed to scouting through loads of…
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Introduction to Q-Learning
You start at a given position, the starting state . From any state you can go left, right, up or down or stay in the same place provided you don’t cross the premises of the maze. Each action will…
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Q-Learning
In the previous section, we discussed the Value Iteration algorithm which requires accessing the complete Markov decision process (MDP), e.g., the transition and reward functions. In this section, we ...
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A Beginners Guide to Q-Learning
Have you ever blamed or beat at your dog punitively for the wrongful actions once it done? Or have you ever trained a pet and rewarded it for every correct command you asked for? If you are a pet…
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Unlocking the Power of the Q-Learning Algorithm
Let’s have a look at deep Q-learning, that is, the algorithm employed in the DeepMind system to play Atari 2600 games at expert human levels. A basic understanding of how Q-learning works is a…
Read more at Becoming Human: Artificial Intelligence Magazine
Intro to Reinforcement Learning: Q-Learning 101
Q-Learning was first introduced in 1989 by Christopher Watkins as an extension of the dynamic programming paradigm. Q-learning also served as the basis for some of the tremendous achievements of deep…...
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Simple Reinforcement Learning: Q-learning
One of my favorite algorithms that I learned while taking a reinforcement learning course was q-learning. Probably because it was the easiest for me to understand and code, but also because it seemed…...
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Interactive Q learning
While going through the process of understanding Q learning, I was always fascinated by the grid world (the 2D world made of boxes, where agent moves from one box to another and collect rewards)…
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AI Anyone Can Understand: Part 7 - Q-Learning
Make sure you check out the rest of the AI Anyone Can Understand Series Continue reading on Towards AI
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Reinforcement Learning Tutorial Part 1: Q-Learning
This is the first part of a tutorial series about reinforcement learning. We will start with some theory and then move on to more practical things in the next part. During this series, you will not…
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Q-Learning Algorithm: From Explanation to Implementation
In my today’s medium post, I will teach you how to implement the Q-Learning algorithm. But before that, I will first explain the idea behind Q-Learning and its limitation. Please be sure to have some…...
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Applied Reinforcement Learning I: Q-Learning
Understand the Q-Learning algorithm step by step, as well as the main components of any RL-based system Photo by DeepMind on Unsplash We have all experienced a situation in which we have done somethi...
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Reinforcement Learning 101: Q-Learning
Decoding the Math behind Q-Learning, Action-Value Functions, and Bellman Equations, and building them from scratch in Python. Image Generated by DALLE In the previous article, we dipped our toes into...
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Deep Q-Learning
Imagine an agent , bold and curious, exploring a vast, uncharted landscape. Every decision it makes holds the potential for reward, but also risk. This is the world of reinforcement learning, where an...
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Q-Learning : A Maneuver of Mazes
We live in a world of opporunities. Let’s use those opportunities to create a tactical world where you know only how to walk and where to go, but dont know how to reach there. Well, I am clearly…
Read more at Becoming Human: Artificial Intelligence Magazine
Q-learning for beginners
Train an AI to solve the Frozen Lake environment Image by author The goal of this article is to teach an AI how to solve the ❄️Frozen Lake environment using reinforcement learning. Instead of reading...
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Practical Reinforcement Learning — 02 Getting started with Q-learning
This time we will teach our self driving car to drive us home (orange node). We have to be careful though as some streets are under construction (grey node) and we don’t want our car crashing into…
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Applied Reinforcement Learning II: Implementation of Q-Learning
Implementation of the Q-Learning algorithm, and application to OpenAI Gym’s Taxi-v3 environment Photo by Richard Bell on Unsplash The first article in this series introduced the basic concepts and co...
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Deep (Double) Q-Learning
Double Deep Q-Learning is an algorithm that teaches an AI to behave in discrete action spaces. It shows superior performance compared to vanilla Deep Q-Learning.
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Q-Learning Algorithm: How to Successfully Teach an Intelligent Agent to Play A Game?
A detailed explanation of a Reinforcement Learning algorithm called Q-Learning with a step-by-step Python example Continue reading on Towards Data Science
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Q-Network Reinforcement Learning Model
Q-learning is an off-policy reinforcement learning algorithm that seeks to seek out the simplest action to require given this state, hence it’s a greedy approach. It’s considered off-policy because…
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Reinforcement Learning:With Q Learning Implementation in Python
Apart from Supervised and Un-Supervised Learning Algorithms, one of the most intriguing and highly practiced domains of Artificial intelligence in recent years include Reinforcement learning. From…
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Q Learning and Deep Q Networks
The journey to Reinforcement learning continues… It’s time to analyze the infamous Q-learning and see how it became the new standard in the field of AI (with a little help from neural networks)…
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