- title = "Using Cultural Algorithms to Evolve Strategies for Recessionary Markets",
- author = "David A. Ostrowski and Robert G. Reynolds",
- pages = "1780--1785",
- booktitle = "Proceedings of the 2004 IEEE Congress on Evolutionary Computation",
- year = "2004",
- publisher = "IEEE Press",
- month = "20-23 " # jun,
- address = "Portland, Oregon",
- volume = "2",
- keywords = "genetic algorithms, genetic programming, Applications of Cultural Algorithms in Industry and Engineering",
- ISBN = "0-7803-8515-2",
-
DOI = "
doi:10.1109/CEC.2004.1331111",
- abstract = "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.",
-
notes = "CEC 2004 - A joint meeting of the IEEE, the EPS, and
the IEE.
Ford Motor Company, Business Science Group, Research and Advanced Engineering, Dearbom Michigan 48121",
