Chapters in this book

1. Frontmatter i
2. Contents vii
3. Foreword ix
4. 1 Introduction 1
5. 2 An Overview 3
6. 3 Mathematical Preliminaries 20
7. 4 Dynamic Programming under Certainty 42
8. 5 Applications of Dynamic Programming under Certainty 53
9. 6 Deterministic Dynamics 80
10. 7 Measure Theory and Integration 98
11. 8 Markov Processes 131
12. 9 Stochastic Dynamic Programming 147
13. 10 Applications of Stochastic Dynamic Programming 171
14. 11 Strong Convergence of Markov Processes 190
15. 12 Weak Convergence of Markov Processes 198
16. 13 Applications of Convergence Results for Markov Processes 212
17. 14 Laws of Large Numbers 234
18. 15 Pareto Optima and Competitive Equilibria 240
19. 16 Applications of Equilibrium Theory 253
20. 17 Fixed-Point Arguments 270
21. 18 Equilibria in Systems with Distortions 284