Q-Learning Agents, Part 3

A Q-Table greatly simplified the challenge of helping a computer agent “learn” to solve an environment. Unfortunately, this particular approach doesn’t scale well to the kinds of applications I would like to create. To help overcome this next hurdle, we will raise the complexity a bit more as the Frozen Lake environment is approached again, […]

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Q-Learning Agents, Part 2

Telling a computer to perform an action based on an input isn’t too hard. Teaching a computer to learn what action to take based on what it sees is a whole different challenge. Now imagine that the computer wont even know if the action is good or bad until some unknown point in the future […]

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Q-Learning Agents, Part 1

Machine Learning provides us an interesting way to solve special kinds of problems. If you’re just playing around, you may see that creating a good problem to work with can be a lot of work on its own. OpenAI gym has recognized this challenge and provided a great solution. They have created a whole collection […]

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Machine Learning

You may have noticed things have been quiet here recently. The reason is that I have been hard at work trying to learn new things myself. Machine Learning is to blame for my currently distracted state, but if you haven’t looked into it, perhaps I can help you catch the bug too. Why Should You […]

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