Abstract
The problem of computing Pareto optimal solutions with distributed algorithms is considered inn-player games. We shall first formulate a new geometric problem for finding Pareto solutions. It involves solving joint tangents for the players' objective functions. This problem can then be solved with distributed iterative methods, and two such methods are presented. The principal results are related to the analysis of the geometric problem. We give conditions under which its solutions are Pareto optimal, characterize the solutions, and prove an existence theorem. There are two important reasons for the interest in distributed algorithms. First, they can carry computational advantages over centralized schemes. Second, they can be used in situations where the players do not know each others' objective functions.
Similar content being viewed by others
References
T. Başar, Relaxation techniques and asynchronous algorithms for on-line computation of non-cooperative equilibria,Journal of Economic Dynamics and Control 11 (1987) 531–549.
T. Başar, Distributed relaxation-type algorithms for noncooperative games, in:Proceedings of the IFAC Symposium on Dynamic Modelling and Control of National Economies 1, Edinburgh, UK (1989) 111–116.
T. Başar and S. Li, Distributed computation of Nash equilibria in linear-quadratic stochastic differential games,SIAM Journal on Control and Optimization 27 (1989) 563–578.
M.S. Bazaraa and C.M. Shetty,Nonlinear Programming (John Wiley, New York, 1979).
D.P. Bertsekas and J.N. Tsitsiklis,Parallel and Distributed Computation (Prentice-Hall, Englewood Cliffs, NJ, 1989).
A.F. Daughety, ed.,Cournot Oligopoly, (Cambridge University Press, Cambridge, MA, 1988).
H. Ehtamo, M. Verkama and R.P. Hämäläinen. On distributed computation of Pareto solutions for two decision makers.IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems and Humans 26(4) (1996).
J.W. Friedman,Game Theory with Applications to Economics, 2nd ed. (Oxford University Press, New York, 1991).
P.T. Harker, A variational inequality approach for the determination of oligopolistic market equilibrium,Mathematical Programming 30 (1984) 105–111.
C.-L. Hwang and A.S.M. Masud,Multiple Objective Decision Making, Methods and Applications (Springer-Verlag, Berlin, 1979).
S. Kakutani, A generalization of Brouwer's fixed point theorem,Duke Mathematical Journal 8 (1941) 457–459.
E. Kalai and E. Lehrer, Rational learning leads to Nash equilibrium,Econometrica 61 (1993) 1019–1045.
S. Li and T. Başar, Distributed algorithms for the computation of noncooperative equilibria,Automatica 23 (1987) 523–533.
F.H. Murphy, H.D. Sherali and A.L. Soyster, A mathematical programming approach for determining oligopolistic market equilibrium,Mathematical Programming 24 (1982) 92–106.
J.M. Ortega and W.C. Rheinboldt,Iterative Solution of Nonlinear Equations in Several Variables (Academic Press, New York, 1970).
D.K. Osborne, Cartel problems,American Economic Review 66 (1976) 835–844.
G.P. Papavassilopoulos, Iterative techniques for the Nash solution in quadratic games with unknown parrameters,SIAM Journal on Control and Optimization 24 (1986) 821–834.
J. Ruusunen, H. Ehtamo and R.P. Hämäläinen, Dynamic cooperative electricity exchange in a power pool,IEEE Transactions on Systems, Man, and Cybernetics 21 (1991) 758–766.
Y. Sawaragi, H. Nakayama and T. Tanino,Theory of Multiobjective Optimization (Academic Press, Orlando, FL, 1985).
J. Teich, Decision support for negotiations, Ph.D. Dissertation, State University of New York (Buffalo, 1991).
J. Teich and S. Zionts, The resource allocation multiple objective negotiation approach (RAMONA), unpublished manuscript, New Mexico State University (Las Cruces, 1993).
P.-L. Yu,Multiple-Criteria Decision Making (Plenum Press, New York, 1985).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Verkama, M., Ehtamo, H. & Hämäläinen, R.P. Distributed computation of Pareto solutions inn-player games. Mathematical Programming 74, 29–45 (1996). https://doi.org/10.1007/BF02592144
Received:
Revised:
Issue Date:
DOI: https://doi.org/10.1007/BF02592144