Stanford Root

Schedule

Stanford Root

Schedule

MS&E 235B

Reinforcement Learning: Behaviors and Applications (EE 383)

UNITS:3
GRADING:Letter or Credit/No Credit
LEVEL:Graduate
GER:—

The subject of reinforcement learning addresses the design of agents that improve decisions over time while operating within complex environments. This course covers desired agent behaviors and principled scalable approaches to realizing such behavior. Homework assignments primarily involve programming exercises carried out in Colab.

Syllabus not available for this section

Sections

0 Terms
No sections available.

MS&E 235B: Reinforcement Learning: Behaviors and Applications (EE 383)

3 units · Letter or Credit/No Credit

The subject of reinforcement learning addresses the design of agents that improve decisions over time while operating within complex environments. This course covers desired agent behaviors and principled scalable approaches to realizing such behavior. Homework assignments primarily involve programming exercises carried out in Colab.

More MS&E courses

  • MS&E 228: Applied Causal Inference with Machine Learning and AI (CS 288)
  • MS&E 229: Bayesian Linear Regression
  • MS&E 232: Introduction to Game Theory
  • MS&E 232H: Introduction to Game Theory (Accelerated)
  • MS&E 233: Game Theory, Data Science and AI
  • MS&E 235A: Markov Decision Processes (EE 283)
  • MS&E 240: Accounting for Managers and Entrepreneurs (MS&E 140)
  • MS&E 241: Economic Analysis (MS&E 141)
  • MS&E 242: Machine Learning for Algorithmic Trading
  • MS&E 243: Energy and Environmental Policy Analysis
  • MS&E 244: Statistical Arbitrage
  • MS&E 245A: Investment Science

All MS&E courses · All departments