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#Bellman Equations

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Institute for Pure & Applied Mathematics (IPAM)

Solving High-Dimensional Optimal Control Problems with Empirical Tensor Train Approximation

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Explore innovative approaches to solve high-dimensional optimal control problems using Tensor Train approximation, with applications to destabilized viscous Burgers and diffusion equations.
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1 Lesons
47 minutes
On-Demand
Free-Video
Discover AI

Understanding Q* (Q-star) - From Q-Learning to Maximum Entropy Reinforcement Learning

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Delve into the technical foundations of Q* (Q-star), exploring its roots in physics entropy, reinforcement learning principles, and practical applications in machine learning systems.
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13 Lesons
20 minutes
On-Demand
Free-Video
Digi-Key

Introduction to Reinforcement Learning

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Learn reinforcement learning fundamentals and apply them to solve control problems using Python libraries. Hands-on training with cartpole example and challenge to tackle inverted pendulum problem.
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22 Lesons
1 hour 15 minutes
On-Demand
Free-Video
Pascal Poupart

CS885 - Semi-Markov Decision Processes

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Explore semi-Markov decision processes, reinforcement learning, and queueing theory. Learn about Bellman's equation and the option framework for advanced decision-making strategies.
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10 Lesons
36 minutes
On-Demand
Free-Video
Pascal Poupart

Distributional RL

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Explore distributional reinforcement learning, covering return distribution, policy evaluation, and the C51 algorithm, with insights into its advantages and applications in Atari games.
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11 Lesons
23 minutes
On-Demand
Free-Video
Simons Institute

Reinforcement Learning via an Optimization Lens

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Explore reinforcement learning through an optimization lens, covering MDPs, Bellman equations, and novel approaches to solving RL problems using linear programming and primal-dual formulations.
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21 Lesons
47 minutes
On-Demand
Free-Video
Simons Institute

Deep Robust Reinforcement Learning and Regularization

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Explore robust reinforcement learning, addressing uncertainties in deep RL through regularization techniques. Gain insights into robust MDPs, policy evaluation, and uncertainty-aware Bellman equations.
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16 Lesons
31 minutes
On-Demand
Free-Video
Simons Institute

Online Learning in Markov Decision Processes - Part 1

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Explore online learning in Markov Decision Processes, covering theory, algorithms, and optimal strategies for reinforcement learning in dynamic environments.
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15 Lesons
1 hour 26 minutes
On-Demand
Free-Video
Institute for Pure & Applied Mathematics (IPAM)

Nonconvex Homogenization for 1D Controlled Brownian Motion in a Random Potential

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Explores stochastic control of Brownian motion in random potentials, analyzing optimal payoff growth and Bellman equation homogenization. Discusses effective Hamiltonians and distinct control regimes.
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1 Lesons
55 minutes
On-Demand
Free-Video
Yannic Kilcher

Q-Learning: From Basics to Deep Q-Networks

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Explore Q-Learning fundamentals, from Markov Decision Processes to Deep Q-Networks, in this comprehensive overview of reinforcement learning concepts and applications.
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7 Lesons
46 minutes
On-Demand
Free-Video
Serrano.Academy

A Friendly Introduction to Deep Reinforcement Learning, Q-Networks and Policy Gradients

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Friendly exploration of deep reinforcement learning concepts, including Markov decision processes, Q-networks, and policy gradients, using examples and visuals to explain complex ideas.
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12 Lesons
36 minutes
On-Demand
Free-Video
Dave Churchill

Intro to Artificial Intelligence - Markov Decision Process (MDP) - Lecture 17

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Explore Markov Decision Processes (MDPs) in AI, learning algorithmic techniques for modern problem-solving in uncertain environments.
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1 Lesons
45 minutes
On-Demand
Free-Video