How to install Unity ML Agents Release 20 in 2023
In this video, Philipp Dominic Siedler will show you how to install ML-Agents Release 20 for Unity 2022.3 or later, step by step, to train your first Machine Learning project using Unity and Reinforcement Learning.
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AI Learns to Walk (deep reinforcement learning)
This video is from AI Warehouse. In this video an AI named Albert learns how to walk to escape 5 rooms I created. The AI was trained using Deep Reinforcement Learning, a method of Machine Learning which involves rewarding the agent for doing something correctly, and punishing it for doing anything incorrectly. Albert’s actions are […]
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An AI Learns to Play Starcraft 2 with Reinforcement Learning
Interesting video tinkering with reinforcement learning via Stable Baselines 3 and Starcraft 2. Code and model: https://github.com/Sentdex/SC2RL
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Deep Q-Network Solves Cart and Pole – Reinforcement Learning Code Project
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Frank
- March 28, 2022
- agent environment
- AI
- AlphaGo
- artificial intelligence
- artificial neural network
- Bellman equation
- CNN
- Deep Learning
- Deep Q-network
- DQN
- Education
- experience replay
- Machine Learning
- markov decision process
- MDP
- Neural Network
- OpenAI Five
- OpenAI Gym
- policy gradients
- policy network
- Python
- PyTorch
- Q-learning
- Q-value
- Reinforcement Learning
- replay memory
- SGD
- stochastic gradient descent
- Supervised Learning
- TensorFlow
- Tutorial
- Unsupervised Learning
In this episode, learn how to use a deep Q-network to solve the Cart and Pole environment.
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Research talk: Maia Chess: A human-like neural network chess engine
Reid McIlroy-Young, PhD Student, University of Toronto delivers this talk about a uman-like neural network chess Even when machine learning surpasses human ability in a domain, there are many reasons why AI systems that capture human-like behavior would be desirable. For example, humans may want to learn and collaborate, or humans may need to interact […]
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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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