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Lecture 4a: Decision Making under Uncertainty (2-stage Stochastic Programming), DTU
LINMA2491: Stochastic Dual Dynamic Programming
9. Markov Rewards and Dynamic Programming
Lecture 2, 2025, Stochastic finite and infinite horizon DP, approximation in value and policy space
HJB equations, dynamic programming principle and stochastic optimal control 1 - Andrzej Święch
Stochastic dynamic programming, optimization in policy space & DFO’s “precautionary” harvest control
Stochastic Programming Approach to Optimization Under Uncertainty (Part 1)
Warren Powell, Stochastic Optimization Challenges in Energy
Lecture 9, 2025; Rollout and Its Variants for Stochastic and Adaptive Control, Application to Wordle
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Last Updated: October 2, 2026
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Slides, class notes, and related textbook material at web.mit.edu/dimitrib/www/RLbook.html Review of finite horizon of ... Joaquim Dias Garcia ( linkedin.com/in/joaquim-dias-garcia/) Guest Lecture for the Optimal Control & Learning Course ... Course: Decision-making under Uncertainty (2026), Technical University of Denmark (DTU). Instructor: Georgios (George) ... Prof. Andrzej Święch from Georgia Institute of Technology gave a talk entitled "HJB equations, Alex Shapiro (Georgia Tech) simons.berkeley.edu/talks/tbd-186 Theory of Reinforcement Learning Boot Camp. ... certainly changes uh and is Hi everyone, Welcome to this video. Rapid technological changes and anthropogenic climate change are responsible for major ...