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JOURNALS // Avtomatika i Telemekhanika

Avtomat. i Telemekh., 2018, Issue 4, Pages 152–166 (Mi at14849)

Stackelberg equilibrium in a dynamic stimulation model with complete information
D. B. Rokhlin, G. A. Ougolnitsky

References

1. von Stackelberg H., Marktform und Gleichgewicht, Springer, Vienna, 1934
2. Basar T., Olsder G. J., Dynamic noncooperative game theory, SIAM, Philadelphia, 1999  mathscinet  zmath
3. Dockner E., Jørgensen S., Van Long N., Sorger G., Differential games in economics and management science, Cambridge University Press, Cambridge, 2000  mathscinet  zmath
4. Van Long N., A survey of dynamic games in economics, World Scientific, Singapore, 2010  mathscinet
5. Li T., Sethi S. P., “A Review of Dynamic Stackelberg Game Models”, Discrete Cont. Dyn.-B, 22:1 (2017), 125–159  mathscinet  zmath
6. Ho Y.-C., Luh P., Muralidharan R., “Information Structure, Stackelberg Games, and Incentive Controllability”, IEEE Trans. Automat. Control, 26:2 (1981), 454–460  crossref  mathscinet  zmath
7. Olsder G. J., “Phenomena in Inverse Stackelberg Games. Part 1: Static Problems”, J. Optim. Theory Appl., 143:3 (2009), 589–600  crossref  mathscinet  zmath
8. Olsder G. J., “Phenomena in Inverse Stackelberg Games. Part 2: Dynamic Problems”, J. Optim. Theory Appl., 143:3 (2009), 601–618  crossref  mathscinet  zmath
9. Groot N., De Schutter B., Hellendoorn H., “Reverse Stackelberg Games. Part I: Basic Framework”, Control Applications (CCA), 2012 IEEE Int. Conf. on Control Applications, 2012, 421–426
10. Groot N., De Schutter B., Hellendoorn H., “Reverse Stackelberg Games. Part II: Results and Open Issues”, Control Applications (CCA), 2012 IEEE Int. Conf. on Control Applications, 2012, 427–432
11. Germeier Yu. B., “Ob igrakh dvukh lits s fiksirovannoi posledovatelnostyu khodov”, Dokl. AN SSSR, 198:5 (1971), 1001–1004  mathnet  mathscinet  zmath
12. Germeier Yu. B., Igry s neprotivopolozhnymi interesami, Nauka, M., 1976  mathscinet
13. Kononenko A. F., “Game-theory Analysis of a Two-level Hierarchical Control System”, USSR Comput. Math. Mathemat. Physics, 14:5 (1974), 72–81  mathnet  crossref  mathscinet  zmath
14. Gorelov M. A., Kononenko A. F., “Dynamic Models of Conflicts. III. Hierarchical Games”, Autom. Remote Control, 76:2 (2015), 264–277  mathnet  crossref  mathscinet  zmath  elib  elib
15. Shen H., Ba şar T., “Incentive-Based Pricing for Network Games with Complete and Incomplete Information”, Advances in Dynamic Game Theory: Numerical Methods, Algorithms, and Applications to Ecology and Economics, eds. Jørgensen S., Quincampoix M., Vincent Th. L., Birkhäuser, Boston, 2007, P. 431–458  mathscinet
16. Staňková K., Olsder G. J., Bliemer M. C. J., “Comparison of Different Toll Policies in the Dynamic Second-best Optimal Toll Design Problem. Case study on a three-link network”, Eur. J. Transp. Infrast. Res., 4:9 (2009), 331–346
17. Luh P., Ho Y., Muralidharan R., “Load Adaptive Pricing: An Emerging Tool for Electric Utilities”, IEEE Trans. Autom. Control, 27:2 (1982), 320–329  crossref  mathscinet  zmath  adsnasa
18. Burkov V. N., Goubko M., Korgin N., Novikov D., Introduction to theory of control in organizations, CRC Press, Boca Raton, 2015  mathscinet  zmath
19. Novikov D. A., Stimulirovanie v sotsialno-ekonomicheskikh sistemakh (bazovye matematicheskie modeli), IPU RAN, M., 1998
20. Novikov D. A., Shokhina T. E., “Incentive Mechanisms in Dynamic Active Systems”, Autom. Remote Control, 64:12 (2003), 1912–1921  mathnet  crossref  mathscinet  zmath
21. Sundaram R. K., A first course in optimization theory, Cambridge University Press, Cambridge, 1996  mathscinet  zmath
22. Papageorgiou N. S., Kyritsi-Yiallourou S. Th., Handbook of applied analysis, Springer, Dordrecht, 2009  mathscinet  zmath
23. Hernández-Lerma O., Lasserre J. B., Discrete-time Markov control processes: basic optimality criteria, Springer, N.Y., 1996  mathscinet
24. Maitra A., “Discounted dynamic programming on compact metric spaces”, Sankhyā: Indian J. Statist. Ser. A, 30:2 (1968), 211–216  mathscinet  zmath
25. Schäl M., “Average Optimality in Dynamic Programming with General State Space”, Math. Oper. Res., 18:1 (1993), 163–172  crossref  mathscinet  zmath
26. Bertsekas D., Shreve S., Stochastic optimal control: the discrete time case, Athena Sci., Belmont, 1996  mathscinet
27. Feinberg E. A., Lewis M. E., “Optimality Inequalities for Average Cost Markov Decision Processes and the Stochastic Cash Balance Problem”, Math. Oper. Res., 32:4 (2007), 769–783  crossref  mathscinet  zmath
28. Cruz-Suárez D., Montes-de-Oca R., Salem-Silva F., “Conditions for the Uniqueness of Optimal Policies of Discounted Markov Decision Processes”, Math. Oper. Res., 60:3 (2004), 415–436  crossref  mathscinet  zmath
29. Breton M., Alj A., Haurie A., “Sequential Stackelberg Equilibria in Two-person Games”, J. Optim. Theory Appl., 59:1 (1998), 71–97  crossref  mathscinet
30. Blackwell D., “Discounted Dynamic Programming”, Ann. Math. Statist., 36:1 (1965), 226–235  crossref  mathscinet  zmath
31. Shreve S. E., Bertsekas D. P., “Universally Measurable Policies in Dynamic Programming”, Math. Oper. Res., 4:1 (1979), 15–30  crossref  mathscinet  zmath
32. Morgan J., “Constrained well-posed two-level optimization problems”, Nonsmooth optimization and related topics, eds. Clarke F. H., Dem'yanov V. F., Giannessi F., Springer, Boston, 1989, 307–325  crossref  mathscinet  adsnasa
33. Patrone F., “Well-posedness for Nash equilibria and related topics”, Recent developments in well-posed variational problems, eds. Lucchetti R., Revalski J., Springer, Dordrecht, 1995, 211–227  crossref  mathscinet
34. Montes-De-Oca R., Lemus-Rodríguez E., “When are the Value Iteration Maximizers Close to an Optimal Stationary Policy of a Discounted Markov Decision Process? Closing the Gap between the Borel Space Theory and Actual Computations”, WSEAS Trans. Math., 9:3 (2010), 151–160  mathscinet


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