Practical Reinforcement LearningHigher School of Economics I am very proud that I survived and completed this thorny but...

Exploration is needed to find unknown actions which lead to very large rewards. Most of the reinforcement learning...

The problems of value-based methods The idea behind value-based reinforcement learning (say, Q-learning) is to find an optimal...

Deep Q-Network (DQN) is the first successful application of learning, both directly from raw visual inputs as humans...

Deduction to supervised learning problem In tabular method, each Q(s, a) could be seen as a parameter. There...

Value Iteration in real world n real world, we don’t have the state transition probability distribution or the...

Reward That all of what we mean by goals and purposes can be well thought of as maximization...

Andrew Ng Anna Koop Brenda Gunderson Computer Communications Specialization Cryptography Differential Equations for Engineers Economics of Money and Banking Evgenii Vashukevich Foundations of Quantum Mechanics Garud Iyengar Ivan Vybornyi Jeffrey Chasnov John Daily Jonathan Katz Kevin Webster Ling-Chieh Kung Machine Learning: Algorithms in the Real World Martin Haugh Mathematics for Engineers Specialization Matthew Hutchens Michael Donohoe Michael Fricke Microsoft Azure Fundamentals AZ-900 Exam Prep Specialization Operations Research (3): Theory Perry Mehrling Petro Lisowsky Physical Basics of Quantum Computing Practical Reinforcement Learning Rebekah May Search Engine Optimization (SEO) Specialization Sergey Sysoev Statistical Thermodynamics Specialization Statistics with Python Specialization Taxation of Business Entities I: Corporations TensorFlow 2 for Deep Learning Specialization U.S. Federal Taxation Specialization Understanding Modern Physics I: Relativity and Cosmology Wounjhang Park Xiaobo Zhou Yi Wang

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