Advanced Topics in Systems, Control and Learning 1 (048715)

Monte Carlo Methods for Computation and Optimization

Nahum Shimkin
Spring 2015

 

Syllabus (pdf)

2015 Lecture Notes:

  Lecture 1 : Introduction

  Lecture 2: Random Variable Generation

  Lecture 3: Variance Reduction Methods, I

  Lecture 4: Importance Sampling

  Lecture 5: Sequetial Importance Sampling; Slides for section 5.3: Particle Filters

  Lecture 6: Markov Chain Monte Carlo

  Lecture 7: Some Topics in Brief

 

Final Assignments

 

Homework:

         Problem Set 1 Submission April 29.

         Problem Set 2 (parts a+b). Submission June 3

         Problem Set 3 Submission June 24

 

Homework and Assignment Grades

 

Slides of Student Presentations:

         Ariel: Simulated Annealing for Constrained Global Optimization

         Ayal: N-grams in MC Tree Search

         Gal: Modern Floor Planning with Simulated Annealing

         Nir: Reversible Jump Markov Chain Monte Carlo

         Niv: MC Simulation of Security Prices

         Oron: Computing Approximate Nash Equilibria

         Noam: Cross Entropy for Monte Carlo Trees Search