Reinforcement Learning and Architectures of Intelligence - Part 1
Explore reinforcement learning and intelligence architectures with Microsoft Research's Ida Momennejad in this comprehensive tutorial from IPAM's Mathematics of Intelligences series.
Introduction to Reinforcement Learning Theory and Methods - Lecture 1
Master the fundamentals of reinforcement learning through theoretical concepts and practical applications, covering Markov decision processes, dynamic programming, and temporal differences with hands-on exercises.
A Short Course on Reinforcement Learning - Lecture 2
Master the fundamentals of reinforcement learning through comprehensive lectures covering Markov decision processes, dynamic programming, and temporal differences, with hands-on practical applications.
How to Use Mean-Field Control for Restless Bandits and Weakly Coupled MDPs
Explore mean-field control techniques for resource allocation in weakly coupled MDPs and restless bandits, focusing on LP-based relaxations and asymptotic optimality.
Introduction to Artificial Intelligence - Reinforcement Learning - Lecture 14
Explore reinforcement learning fundamentals in AI, covering key concepts and techniques for problem-solving in modern environments.
Intro to Artificial Intelligence - RL Monte Carlo Methods - Lecture 18
Explore Monte Carlo methods in reinforcement learning, applying algorithmic techniques to solve AI problems in gaming environments.
Sequential Learning in Artificial Intelligence - Oral Session 4
Explore cutting-edge research in sequential learning, covering robust reinforcement learning, online learning in MDPs, fairness in predict-then-optimize settings, and constrained POMDPs.