Subject archive for "reinforcement-learning"


Reinforcement learning: The K-armed bandit problem

In a previous blog post we talked about the foundations of reinforcement learning. We covered classical and operant conditioning, rewards, states, and actions, and did a review of some common reinforcement learning use-cases. This entry is a continuation of the series. In it, we present the k-armed bandit problem - a very simple setting that enables us to introduce the interaction between some of the key components of reinforcement learning.

By Nikolay Manchev9 min read

Machine Learning

Deep reinforcement learning

This article provides an excerpt "Deep Reinforcement Learning" from the book, Deep Learning Illustrated by Krohn, Beyleveld, and Bassens. The article includes an overview of reinforcement learning theory with focus on the deep Q-learning. It also covers using Keras to construct a deep Q-learning network that learns within a simulated video game environment. Many thanks to Addison-Wesley Professional for the permission to excerpt the chapter.

By John Joo58 min read

Machine Learning

Semi-uniform strategies for solving K-armed bandits

In a previous blog post we introduced the K-armed bandit problem - a simple example of allocation of a limited set of resources over time and under uncertainty. We saw how a stochastic bandit behaves and demonstrated that pulling arms at random yields rewards close to the expectation of the reward distribution.

By Nikolay Manchev6 min read

Reinforcement Learning

What Is Reinforcement Learning and How Is It Used?

When you do something well, you’re rewarded. This simple principle has guided humans since the beginning of time, and now, more than ever before, it is the key principle behind a growing number of reinforcement learning (RL) agents within the technologies we use and rely upon every day.

By David Weedmark8 min read

Data Science

Evaluating Ray: Distributed Python for Massive Scalability

Dean Wampler provides a distilled overview of Ray, an open source system for scaling Python systems from single machines to large clusters. If you are interested in additional insights, register for the upcoming Ray Summit.

By Dean Wampler14 min read

Data Science

Themes and Conferences per Pacoid, Episode 2

Paco Nathan's column covers themes of data science for accountability, reinforcement learning challenges assumptions, as well as surprises within AI and Economics.

By Paco Nathan30 min read

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