Sequential Decision Analytics Lecture with Warren Powell
Microsoft Research recently had Warren Powell speak on Sequential Decision Analytics: A unified framework Warren Powell is Professor Emeritus at Princeton University and Chief Analytics Officer of Optimal Dynamics. He’s also Founder and Director of Castle Labs at Princeton which manages over 70 grants and contracts with government agencies and leading companies working to develop […]
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A Beginner’s Guide to Reinforcement Learning
Reinforcement learning is one of the most exciting collections of techniques for building self-learning systems. Over the past five years, we’ve seen RL successfully meet such challenges as exceeding human performance on popular video games and board games. Despite the excitement around the success of these RL agents, it has remained extraordinarily difficult for most […]
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Reinforcement Learning: Machine Learning Meets Control Theory
Steve Brunton explains reinforcement learning. Reinforcement learning is a powerful technique at the intersection of machine learning and control theory, and it is inspired by how biological systems learn to interact with their environment. In this video, we provide a high level overview of reinforcement learning, along with leading algorithms and impressive applications.
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Provably Efficient Reinforcement Learning with Dr. Akshay Krishnamurthy
MSR’s New York City lab is home to some of the best reinforcement learning research on the planet but if you ask any of the researchers, they’ll tell you they’re very interested in getting it out of the lab and into the real world. One of those researchers is Dr. Akshay Krishnamurthy and today, he […]
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Get Started with Reinforcement Learning on Azure Machine Learning
Are you curious how data scientists and researchers train agents that make decisions? Learn how to use reinforcement learning to optimize decision making using Azure Machine Learning. We show you how to get started. Time Index: [00:36] – What is reinforcement learning? [01:37] – How do reinforcement learning algorithms work? [04:10] – Reinforcement Learning on […]
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Top 10 Free Resources To Learn Reinforcement Learning
Reinforcement Learning (RL) uses a “trial and error” method and interacts with the environment to learn an optimal policy for gaining maximum rewards by making the right decisions. It is one of the most popular machine learning techniques among organizations to develop solutions like recommender systems, healthcare, robotics, and many more. Analytics India Magazine has […]
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Building a Better AI than Nintendo
The other day Jabrils was playing a Nintendo game & the AI was so abysmal that he stormed to his computer & make a better one than Nintendo.
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David Silver on AlphaGo, AlphaZero, and Deep Reinforcement Learning
Lex Fridman interviews David Silver for the Artificial Intelligence podcast.. David Silver leads the reinforcement learning research group at DeepMind and was lead researcher on AlphaGo, AlphaZero and co-lead on AlphaStar, and MuZero and lot of important work in reinforcement learning. Time Index: 0:00 – Introduction 4:09 – First program 11:11 – AlphaGo 21:42 – […]
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Robot Learns to Self Balance with N Step SARSA
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Frank
- April 3, 2020
- artificial intelligence
- artificial intelligence openai gym
- artificial intelligence python
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- cartpole python
- monte carlo methods
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- Reinforcement Learning
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- sarsa cartpole
- sarsa open ai gym
- temporal difference
Machine Learning with Phil explores reinforcement learning with SARSA in this video. While Q learning is a powerful algorithm, SARSA is equally powerful for many environments in the open AI gym. In this complete reinforcement learning tutorial, I’ll show you how to code an n Step SARSA agent from scratch. n Step temporal difference learning […]
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Deep Q Learning is Simple with PyTorch
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Frank
- March 24, 2020
- deep q learning
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- deep q learning agent
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- Q Learning
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- Reinforcement Learning
Machine Learning with Phil has a great tutorial on how to do Deep Q Learning in PyTorch. The PyTorch deep learning framework makes coding a deep q learning agent in python easier than ever. We’re going to code up the simplest possible deep Q learning agent, and show that we only need a replay memory […]
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