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Reinforcement Learning: Machine Learning Meets Control Theory
Steve Brunton
12 ก.พ. 2021
การดู 246,748 ครั้ง
Deep Reinforcement Learning: Neural Networks for Learning Control Laws
Reinforcement Learning Series: Overview of Methods
Everything You Need to Know About Control Theory
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AI/ML+Physics Part 1: Choosing what to model [Physics Informed Machine Learning]
Nonlinear Control: Hamilton Jacobi Bellman (HJB) and Dynamic Programming
Model Based Reinforcement Learning: Policy Iteration, Value Iteration, and Dynamic Programming
AI/ML+Physics Part 3: Designing an Architecture [Physics Informed Machine Learning]
Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 1 - Introduction - Emma Brunskill
AI/ML+Physics Part 2: Curating Training Data [Physics Informed Machine Learning]
Neural Network Architectures & Deep Learning
Something Strange Happens When You Follow Einstein's Math
Q-Learning: Model Free Reinforcement Learning and Temporal Difference Learning
A Neural Network Primer
AI vs. AI in 100m Dash (deep reinforcement learning)
Overview of Deep Reinforcement Learning Methods
AI/ML+Physics Part 5: Employing an Optimization Algorithm [Physics Informed Machine Learning]
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What Is Reinforcement Learning?
An introduction to Reinforcement Learning