Learning the optimum as a Nash equilibrium

DOI10.1016/S0165-1889(99)00012-3zbMath0994.93011OpenAlexW2060470081MaRDI QIDQ1605707

Süheyla Özyıldırım, Nedim M. Alemdar

Publication date: 23 July 2002

Published in: Journal of Economic Dynamics \& Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0165-1889(99)00012-3

zbMATH Keywords

Nash equilibriumgenetic algorithmsnoncooperative gameglobal optimum\(k\)-person dynamic game

Mathematics Subject Classification ID

Noncooperative games (91A10) Applications of game theory (91A80) (n)-person games, (n>2) (91A06) Decentralized systems (93A14) Parallel numerical computation (65Y05) Dynamic games (91A25)

Related Items (4)

Feedback approximation of the stochastic growth model by genetic neural networks ⋮ Multi-objective design method based on evolution game and its application for suspension ⋮ On-line computation of Stackelberg equilibria with synchronous parallel genetic algorithms ⋮ Saddle-point calculation for constrained finite Markov chains

Cites Work

• Money as a medium of exchange in an economy with artificially intelligent agents
• A genetic game of trade, growth and externalities
• Dynamic noncooperative game theory
• Genetic algorithm learning and the cobweb model
• Hybrid algorithms with automatic switching for solving nonlinear equation systems
• Discrete-Time Finite Horizon Approximation of Infinite Horizon Optimization Problems with Steady-State Invariance
• A Nongradient and Parallel Algorithm for Unconstrained Minimization
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