DeepMind Introduces Reinforcement Learning Lecture Series 2021, Here’s What You Can Learn
Researchers from Google DeepMind have collaborated with the University College London (UCL) to offer students a comprehensive introduction to modern reinforcement learning. The series comprises 13 lectures covering the fundamentals of reinforcement learning and planning in sequential decision problems before progressing to more advanced topics and modern deep RL algorithms. DeepMind Research Scientists and Engineers Hado van Hasselt, Diana Borsa, and Matteo Hessel lead a 13-part self-contained introduction to RL and deep RL, aimed at students at Master’s level and above. The 13 lecture series includes: Introduction to Reinforcement LearningExploration & ControlMDPs & Dynamic ProgrammingTheoretical Fundamentals of Dynamic Programming AlgorithmsModel-free PredictionModel-free ControlFunction ApproximationPlanning & modelsPolicy-Gradient & Actor-Critic methodsApproximate Dynamic ProgrammingMulti-step & Off PolicyDeep Reinforcement Learning #1Deep Reinforcement Learning #2 Introducing the '21 DeepMind x @ai_ucl Reinforcement Learning Lecture Series, a comprehensive introduction to modern RL.Follow along with our researchers are they explore Markov Decision Processes, sample-based learning algorithms & much more: https://t.co/vGaQ4ryIBD 1/2 pic.twitter.com/XmnwpeY5CB— Google DeepMind (@GoogleDeepMind) September 9, 2021 The programme is designed with an aim to give students a detailed understanding of various topics, including Markov Decision Processes, sample-based learning algorithms (e.g. (double) Q-learning, SARSA), deep reinforcement learning, and more. It also explores more advanced topics like off-policy learning, multi-step updates and eligibility traces, as well as conceptual and practical considerations in implementing deep reinforcement learning algorithms such as rainbow DQN. In a recent set of events, the Alphabet-owned research lab DeepMind announced that it is making AlphaFold 2.0 source code public. This AI-based algorithm predicts the shape of proteins, a major challenge in the healthcare and life sciences field. With this decision, DeepMind hopes to offer easy access and better research opportunities to the scientific community in areas such as drug discovery.
The series comprises 13 lectures covering the fundamentals of reinforcement learning and planning in sequential decision problems before progressing to more advanced topics and modern deep RL algorithms.
The series comprises 13 lectures covering the fundamentals of reinforcement learning and planning in sequential decision problems.
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Kumar Gandharv, PGD in English Journalism (IIMC, Delhi), is setting out on a journey as a tech Journalist at AIM. A keen observer of National and IR-related news.