Reinforcement Learning Archives - Page 2 of 3 - Open Data Science - Your News Source for AI, Machine Learning & more

How to Make Sense of the Reinforcement Learning Agents? What and Why I Log During Training and Debug

Machine Learning Modeling Reinforcement Learningposted by ODSC Community October 22, 2020

Based on simply watching how an agent acts in the environment, it is hard to tell anything about why it behaves this way and how it works internally. That’s why it is crucial to establish metrics that tell WHY the agent performs in a certain way.... Read more

Reinforcement Learning with Ray RLlib

Machine Learning Modeling Europe 2020 Reinforcement Learningposted by ODSC Community July 30, 2020

Why Reinforcement Learning? In reinforcement learning (RL), an agent tries to maximize a reward while interacting with an environment. The agent observes the state of the environment, takes an action and observes the reward received (if any) and the new state. Then the agent takes the... Read more

Explore Fundamental Concepts of Reinforcement Learning

Machine Learning Modeling Reinforcement Learningposted by ODSC Community April 6, 2020

This article is an excerpt from the book Mastering Machine Learning Algorithms, Second Edition by Giuseppe Bonaccorso, a newly updated and revised edition of the bestselling guide to exploring and mastering the most important algorithms for solving complex machine learning problems. This article helps you understand... Read more

Deep Q-Learning Algorithm in Reinforcement Learning

Deep Learning Modeling Neural Networks Reinforcement Learningposted by ODSC Community February 21, 2020

In this article, we will discuss Q-learning in conjunction with neural networks (NNs). This combination has the name deep Q-network (DQN). This article is an excerpt from the book Deep Reinforcement Learning Hands-on, Second Edition by Max Lapan. This book provides you with an introduction to the... Read more

Best Deep Reinforcement Learning Research of 2019

Data Science Academic Research Deep Learning Modeling deep reinforcement learning Reinforcement Learningposted by Daniel Gutierrez, ODSC January 15, 2020

Since my mid-2019 report on the state of deep reinforcement learning (DRL) research, much has happened to accelerate the field further. Read my previous article for a bit of background, brief overview of the technology, comprehensive survey paper reference, along with some of the best research... Read more

What You Need to Know about DeepMind’s BSuite

Data Science Academic Research Deep Learning bsuite deepmind Reinforcement Learningposted by Elizabeth Wallace, ODSC October 11, 2019

Imagine this. You know that reinforcement learning has been responsible for some of AI’s most significant advancements. You’re in the exploratory phase of implementing your first project. You’d love a way to evaluate whether your RL agent is appropriate for the task you have, something not... Read more

Behavior Suite for Reinforcement Learning

Data Science Academic Research Deep Learning Modeling bsuite Reinforcement Learningposted by ODSC Team October 9, 2019

A team from DeepMind Technologies—made up of Ian Osband, Yotam Doron, Matteo Hessel, John Aslanides, Eren Sezner, Andre Saraiva, Katrina McKinney, Tor Lattimore, Csaba Szepezvari, Satinder Singh, Benjamin Van Roy, Richard Sutton, David Silver, and Hado Van Hesselt—has recently published a piece on their new program... Read more

Best Deep Reinforcement Learning Research of 2019 So Far

Data Science Academic Research Deep Learning Modeling deep reinforcement learning Reinforcement Learningposted by Daniel Gutierrez, ODSC August 21, 2019

In this article, I’ve conducted an informal survey of all the deep reinforcement learning research thus far in 2019 and I’ve picked out some of my favorite papers. This list should make for some enjoyable summer reading! [Related Article: 10 Compelling Machine Learning Dissertations from Ph.D.... Read more

Watch: Imitation Learning: Reinforcement Learning For The Real World

Conferences Deep Learning Imitation Learning Reinforcement Learningposted by ODSC Team August 19, 2019

This talk will introduce the formal Imitation Learning problem and discuss two main categories of agent training in the Imitation Learning paradigm: behavioral cloning and interactive experts. The talk will also include examples of where it could be used to solve real-world problems and a demonstration... Read more

Bears Need to Learn as well – Practical Reinforcement Learning with TensorFlow 2.0 & TF-Agents

Blogs from ODSC Speakers Conferences Modeling ODSC Speaker Reinforcement Learning TensorFlow West 2019posted by Oliver Zeigermann July 25, 2019

Editor’s Note: Oliver is speaking at ODSC West 2019, see his talk “Reinforcement Learning with TF Agents & TensorFlow 2.0: Hands On” there. Have a look at our friend Orso the bear. Orso lives in his cave and knows his area and where he can typically... Read more