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Discipline Module 4 · Prescriptive Methods

Reinforcement Learning

Workload
30h
Professor Prof. Dr. Thiago Silva PhD in Production Engineering from UFMG with doctoral studies at the University of Stirling.
Syllabus

Decision-making under uncertainty. Monte Carlo simulation. Markov decision processes. Approximate dynamic programming. Q-learning. Proximal Policy Optimization (PPO). Applications in industry.

Content
  • Decision-making under uncertainty
  • Monte Carlo simulation
  • Markov decision processes
  • Approximate dynamic programming
  • Q-learning
  • Proximal Policy Optimization (PPO)
  • Applications in industry
Core Bibliography
  • SUTTON, Richard S.; BARTO, Andrew G. Reinforcement learning: An introduction. MIT press, 2018.
  • BERTSEKAS, Dimitri P. et al. Dynamic programming and optimal control. Belmont, MA: Athena scientific, 2005.
  • POWELL, Warren B. Approximate Dynamic Programming: Solving the curses of dimensionality. John Wiley & Sons, 2011.
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