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Agent-based modelling of product invention
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Source Genetic And Evolutionary Computation Conference archive
Proceedings of the 2005 conference on Genetic and evolutionary computation table of contents
Washington DC, USA
SESSION: Artificial life, evolutionary robotics, and adaptive behavior table of contents
Pages: 129 - 136  
Year of Publication: 2005
ISBN:1-59593-010-8
Authors
Anthony Brabazon  University College Dublin, Dublin, Ireland
Arlindo Silva  Instituto Politecnico de Castelo, Branco, Portugal
Tiago Ferra de Sousa  Instituto Politecnico de Castelo, Branco, Portugal
Michael O'Neill  University of Limerick, Limerick, Ireland
Robin Matthews  Kingston University, London, UK
Ernesto Costa  Universidade de Coimbra, Coimbra, Portugal
Sponsors
SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

This study describes a novel simulation model of the process of product invention. Invention is conceptualized as a process of directed evolutionary adaptation, on a landscape of product design possibilities, by a population of profit-seeking agents (inventors). The simulation experiments examine the sensitivity of the rate of advance in product fitness to the choice of search heuristics employed by inventors. The key finding of the experiments is that if search heuristics are confined to those which are rooted in past experience, or to heuristics which merely generate variety, limited product advance occurs. Notable product fitness advance only occurs when inventor's expectations as to the relative fitness of potential product inventions are incorporated into the model of invention. The results demonstrate the importance of human direction and expectations in invention. They also support the importance of formal product / project evaluation procedures in organizations, and the importance of market information when inventing new products.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Anthony Brabazon: colleagues
Arlindo Silva: colleagues
Tiago Ferra de Sousa: colleagues
Michael O'Neill: colleagues
Robin Matthews: colleagues
Ernesto Costa: colleagues