Съдържание:
  • An overview
  • Mathematical preliminaries
  • Dynamic programming under certainty
  • Applications of dynamic programming under certainty
  • Deterministic dynamics
  • Measure theory and integration
  • Markov processes
  • Stochastic dynamic programming
  • Applications of stochastic dynamic programming
  • Strong convergence of Markov processes
  • Weak convergence of Markov processes
  • Applications of convergence results for Markov processes
  • Laws of large numbers
  • Pareto optima and competitive equilibria
  • Applications of equilibrium theory
  • Fixed-point arguments
  • Equilibria in systems with distortions.