Deepmind X Ucl Rl Lecture Series Exploration Control 2 13

June 1, 2026
Search Snapshot: Research Scientist Hado van Hasselt takes a closer look at model-free prediction and its relation to Monte Carlo and temporal ... Research Scientist Hado van Hasselt explains how to combine deep learning with reinforcement learning for "deep reinforcement ...

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General Context Overview

Research Engineer Matteo Hessel explains how to learn and use models, including algorithms like Dyna and Monte-Carlo tree ... Research Scientist Hado van Hasselt discusses multi-step and off policy algorithms, including various techniques for variance ...

Guide Background

Research Scientist Hado van Hasselt explains how to combine deep learning with reinforcement learning for "deep reinforcement ... Research Scientist Hado van Hasselt looks at why it's important for learning agents to balance Research Scientist Hado van Hasselt covers policy algorithms that can learn policies directly and actor critic algorithms that ...

Guide Review Notes

Research Scientist Hado van Hasselt covers policy algorithms that can learn policies directly and actor critic algorithms that ... Research Engineer Matteo Hessel covers general value functions, GVFs as auxiliary tasks, and explains how to deal with scaling ...

Reference Useful Details

Research Scientist Hado van Hasselt introduces the reinforcement learning course and explains how reinforcement learning ... Research Scientist Hado van Hasselt takes a closer look at model-free prediction and its relation to Monte Carlo and temporal ... Research Scientist Hado van Hasselt covers prediction algorithms for policy improvement, leading to algorithms that can learn ...

Key points worth scanning

  • Research Engineer Matteo Hessel talks practical considerations and algorithms for deep reinforcement learning, including how to ...
  • Research Scientist Hado van Hasselt looks at why it's important for learning agents to balance
  • Research Scientist Hado van Hasselt explains how to combine deep learning with reinforcement learning for "deep reinforcement ...
  • Research Scientist Hado van Hasselt covers policy algorithms that can learn policies directly and actor critic algorithms that ...
  • Research Engineer Matteo Hessel covers general value functions, GVFs as auxiliary tasks, and explains how to deal with scaling ...

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Supporting Gallery

DeepMind x UCL RL Lecture Series - Exploration & Control [2/13]
DeepMind x UCL RL Lecture Series - Deep Reinforcement Learning #2 [13/13]
DeepMind x UCL RL Lecture Series - Introduction to Reinforcement Learning [1/13]
DeepMind x UCL RL Lecture Series - Planning & models [8/13]
DeepMind x UCL RL Lecture Series - Function Approximation [7/13]
DeepMind x UCL RL Lecture Series - Model-free Prediction [5/13]
DeepMind x UCL RL Lecture Series - Model-free Control [6/13]
DeepMind x UCL RL Lecture Series - Policy-Gradient and Actor-Critic methods [9/13]
DeepMind x UCL RL Lecture Series - Multi-step & Off Policy [11/13]
DeepMind x UCL RL Lecture Series - Deep Reinforcement Learning #1 [12/13]
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Useful Guides

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Browse More Notes
DeepMind x UCL RL Lecture Series - Exploration & Control [2/13]

DeepMind x UCL RL Lecture Series - Exploration & Control [2/13]

Research Scientist Hado van Hasselt looks at why it's important for learning agents to balance

DeepMind x UCL RL Lecture Series - Deep Reinforcement Learning #2 [13/13]

DeepMind x UCL RL Lecture Series - Deep Reinforcement Learning #2 [13/13]

Research Engineer Matteo Hessel covers general value functions, GVFs as auxiliary tasks, and explains how to deal with scaling ...

DeepMind x UCL RL Lecture Series - Introduction to Reinforcement Learning [1/13]

DeepMind x UCL RL Lecture Series - Introduction to Reinforcement Learning [1/13]

Research Scientist Hado van Hasselt introduces the reinforcement learning course and explains how reinforcement learning ...

DeepMind x UCL RL Lecture Series - Planning & models [8/13]

DeepMind x UCL RL Lecture Series - Planning & models [8/13]

Research Engineer Matteo Hessel explains how to learn and use models, including algorithms like Dyna and Monte-Carlo tree ...

DeepMind x UCL RL Lecture Series - Function Approximation [7/13]

DeepMind x UCL RL Lecture Series - Function Approximation [7/13]

Research Scientist Hado van Hasselt explains how to combine deep learning with reinforcement learning for "deep reinforcement ...

DeepMind x UCL RL Lecture Series - Model-free Prediction [5/13]

DeepMind x UCL RL Lecture Series - Model-free Prediction [5/13]

Research Scientist Hado van Hasselt takes a closer look at model-free prediction and its relation to Monte Carlo and temporal ...

DeepMind x UCL RL Lecture Series - Model-free Control [6/13]

DeepMind x UCL RL Lecture Series - Model-free Control [6/13]

Research Scientist Hado van Hasselt covers prediction algorithms for policy improvement, leading to algorithms that can learn ...

DeepMind x UCL RL Lecture Series - Policy-Gradient and Actor-Critic methods [9/13]

DeepMind x UCL RL Lecture Series - Policy-Gradient and Actor-Critic methods [9/13]

Research Scientist Hado van Hasselt covers policy algorithms that can learn policies directly and actor critic algorithms that ...

DeepMind x UCL RL Lecture Series - Multi-step & Off Policy [11/13]

DeepMind x UCL RL Lecture Series - Multi-step & Off Policy [11/13]

Research Scientist Hado van Hasselt discusses multi-step and off policy algorithms, including various techniques for variance ...

DeepMind x UCL RL Lecture Series - Deep Reinforcement Learning #1 [12/13]

DeepMind x UCL RL Lecture Series - Deep Reinforcement Learning #1 [12/13]

Research Engineer Matteo Hessel talks practical considerations and algorithms for deep reinforcement learning, including how to ...