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Related lectures (10)

Model-Based Deep Reinforcement Learning: Monte Carlo Tree Search

Explores model-based deep reinforcement learning, focusing on Monte Carlo Tree Search and its applications in game strategies and decision-making processes.

Alpha Go: Machine Learning and Game Strategies

Explores the historical perspective and development of the AlphaGo algorithm, focusing on machine learning and game strategies.

Chess Positions

Explores different chess positions and historical battle tactics, ending with a musical performance.

Creativity in Science

Explores the essence of science, creativity, and problem-solving through personal reflections and illustrative examples.

Positions in Chess: Understanding Strategies

Explores different chess positions and strategic gameplay, accompanied by musical interpretations of library books.

Approximation and Compound Interest

Explores evaluation methods, raising numbers to a power, chess game origins, and compound interest calculations.

Multistage Games: Extensive Form and Feedback Strategies

Explores multistage games, focusing on extensive form and feedback strategies, including Nash equilibria and backward induction methods.

Deep Q-Learning: DeepRL1.1

Covers Deep Q-learning in deep neural networks, its application in games, backpropagation, Q-values, and V-values.

General Introduction into Artificial Neural Networks: part 3

Covers learning by rewards in deep reinforcement learning without math details.

First steps toward deep reinforcement learning

Explores the shift to deep reinforcement learning through neural networks for direct policy learning, bypassing Q-values and V-values.

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