1. Introduction 2
Basics of Monte Carlo methods 3
Basics of standard optimal stopping, multiple stopping, and optimal control problem 4
Dual representations for standard optimal stopping, multiple stopping, and optimal control problems. 5
Primal algorithms for optimal stopping problems: regression algorithms, optimization algorithms, policy iteration. Extensions to multiple stopping, examples. 6
Multilevel primal algorithms. 7
Multilevel dual algorithms 8
Convergence analysis of primal algorithms. 9
Convergence analysis of dual algorithms. 10
Consumption based approaches. 11
Dimension reduction for primal algorithms. 12
Variance reduction for dual algorithms. 13
Conclusion.