Agent-based modeling on technological innovation as an evolutionary process. (English) Zbl 1097.91056

Summary: This paper describes a multi-agent model built to simulate the process of technological innovation, based on the widely accepted theory that technological innovation can be seen as an evolutionary process. The actors in the simulation include producers and a large number of consumers. Every producer will produce several types of products at each step. Each product is composed of several design parameters and several performance parameters (fitness components). Kauffman’s famous \(NK\) model is used to deal with the mapping from a design parameter space (DPS) to a performance parameter space (PPS). In addition to the constructional selection, which can be illustrated by the \(NK\) model, we added environmental selection into the simulation and explored technological innovation as the result of the interaction between these two kinds of selection.


91B38 Production theory, theory of the firm
Full Text: DOI


[1] Altenberg, L., Evolving better representations through selective genome growth, Proceedings of the IEEE World Congress on Computational Intelligence, 182-187 (1994)
[2] Audretsch, D. A., Innovation and Industry Evolution (1995), The MIT Press: The MIT Press Cambridge, MA
[3] Axelrod, R., Advancing the art of simulation in the social sciences, Simulating Social Phenomena, 21-40 (1997)
[4] Ballot, G.; Taymaz, E., Technology change, learning and macro-economic coordination: An evolutionary model, Journal of Artificial Societies and Social Simulation, 2, 2 (1999)
[5] Arthur, W. B., Competing Technologies. Technical Change and Economic Theory (1988), Pinter: Pinter London, pp. 590-607
[6] Derek, W. B.; Fernando, S. O., Agent-based simulation-an application to the new electricity trading arrangements of England and Wales, IEEE Transition on Evolutionary Computation, 5, 5, 493-503 (2001)
[7] Doran, J.; Palmer, M.; Gilbert, N.; Mellars, P., The EOS project: Modeling upper Paleolithic social change, (Gilbert, N.; Doran, J., Simulating Societies (1994), UCL Press: UCL Press London), 195-222
[9] Gilbert, N.; Pyka, A.; Ahrweiler, P., Innovation networks-a simulation approach, Journal of Artificial Societies and Social Simulation, 4, 3 (2001)
[10] Goldberg, D. E., Genetic Algorithms in Search Optimization and Machine Learning (1989), Addison-Wesley Publishing Company, Inc. · Zbl 0721.68056
[11] John, M., Active nonlinear tests (ANTs) of complex simulations models, Management Science, 44, 6, 820-830 (1998) · Zbl 0988.90527
[12] Kauffman, S., The Origins of Order: Self-Organization and Selection in Evolution (1993), Oxford University Press
[13] Kauffman, S.; Macready, W., Technological evolution and adaptive organizations, Complexity, 1, 2, 26-43 (1995)
[14] Leydesdorff, L., Technology and culture: The dissemination and the potential “lock-in” of new technologies, Journal of Artificial Societies and Social Simulation, 4, 3 (2001)
[16] Resnick, M. R., Turtles, Termites, and Traffic Jams (1994), MIT Press: MIT Press Cambridge, MA
[17] Roy, B., Using agents to make and manage markets across a supply web: Replacing central, global optimization with a distributed, self-organizing market approach, Complexity, 3, 4, 31-35 (1998)
[18] Rycroft, R. W.; Kash, D. E., The Complexity Challenge-Technological Innovation for the 21st Century (1999), Pinter: Pinter London
[19] Sahal, D., Patterns of Technological Innovation (1981), Addison-Wesley Pub. Co., Advanced Book Program/World Science Division
[20] Stacey, R. D., Complexity and Emergence in Organizations-Learning and Knowledge creation (2001), Routledge: Routledge London
[21] Stankiewicz, R., The Concept of Design Space Technological Innovation as an Evolutionary Process (2000), Cambridge University Press, pp. 234-247
[22] Thomas, O., Computer simulation: The third symbol system, Journal of Experimental Social Psychology, 24, 5, 381-392 (1998)
[24] Wooldridge, M.; Jennings, N., Intelligent agents: Theory and practice, Knowledge Engineering Review, 10, 2, 115-152 (1995)
[25] Ziman, J., Evolutionary Models for Technological Change, Technological Innovation as an Evolutionary Process (2000), Cambridge University Press, pp. 3-12
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.