Using Genetic Algorithms to Model the Evolution of Heterogeneous Beliefs
Computational Economics
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
An analysis of the behavior of a class of genetic adaptive systems.
An analysis of the behavior of a class of genetic adaptive systems.
Nonlinear inertia weight variation for dynamic adaptation in particle swarm optimization
Computers and Operations Research
Robust Evolutionary Algorithm Design for Socio-economic Simulation
Computational Economics
Comparison of Stochastic Global Optimization Methods to Estimate Neural Network Weights
Neural Processing Letters
Implications of a Reserve Price in an Agent-Based Common-Value Auction
Computational Economics
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Particle swarm optimization (PSO) is adapted to simulate dynamic economic games. The robustness and speed of the PSO algorithm is compared to a genetic algorithm (GA) in a Cournot oligopsony market. Artificial agents with the PSO learning algorithm find the optimal strategies that are predicted by theory. PSO is simpler and more robust to changes in algorithm parameters than GA. PSO also converges faster and gives more precise answers than the GA method which was used by some previous economic studies.