Using cultural algorithms to evolve strategies for recessionary markets

摘要

Cultural algorithms are computational self-adaptive models consisting of a population and a belief space. Two cultural algorithms are applied, with one supporting white box testing and the second black box testing. The two populations communicate with each other by means of a shared belief space. This is applied to the calibration of a multi-agent system by allowing for evolution of near optimal parameters. The cultural approach is employed to abstract coefficients of pricing strategies that are applied to a complex model of durable goods. This model simulates consumer behaviors as applied in the context of economic recession.