Abstract
Despite several examples of deployed agent systems, there remain barriers to the large-scale adoption of agent technologies. In order to understand these barriers, this paper considers aspects of marketing theory which deal with diffusion of innovations and their relevance to the agents domain and the current state of diffusion of agent technologies. In particular, the paper examines the role of standards in the adoption of new technologies, describes the agent standards landscape, and compares the development and diffusion of agent technologies with that of object-oriented programming. The paper also reports on a simulation model developed in order to consider different trajectories for the adoption of agent technologies, with trajectories based on various assumptions regarding industry structure and the existence of competing technology standards. We present details of the simulation model and its assumptions, along with the results of the simulation exercises.
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References
Aart, C., van Marcke, K. Pels, R. F., & Smulders, J. L. F. C. (2002). International insurance traffic with software agents. In F. van Harmelen (Ed.), Proceedings of the Fifteenth European Conference on Artificial Intelligence. IOS Press.
Baxter J. and Hepplewhite R. (1999). Agents in tank battle simulations. Communications of the ACM 42(3): 74–75
Bazzan A.L.C. (2005). A distributed approach for coordination of traffic signal agents. Journal of Autonomous Agents and Multiagent Systems 10(2): 131–164
Dahl O.-J. (2002). The roots of object orientation: The Simula language. In: Broy, M. and Denert, E. (eds) Software pioneers: contributions to software engineering. Programming, Software Engineering and Operating Systems Series, pp. Springer, Heidelberg
Dahl, O.-J., & Nygaard, K. (1965). SIMULA: A language for programming and description of discrete event systems. Introduction and user’s manual. Technical Report 11, Norwegian Computing Centre, Oslo, Norway.
Darley, V., & Sanders, D. (2004). An agent-based model of a corrugated-box factory: The trade-off between finished goods stock and on-time-in-full delivery. In H. Coelho & B. Espinasse (Eds.), Proceedings of the Fifth Workshop on Agent-Based Simulation.
Dorer, K., & Calisti, M. (2005). An adaptive solution to dynamic transport optimiation. In M. Pechoucek, D. Steiner, & S. Thompson (Eds.) Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multi-Agent Systems: Industry Track. (pp. 45–51). ACM Press.
Du T.C., Li E.Y. and Chang A.P. (2003). Mobile agents in distributed network management. Communications of the ACM 46(7): 127–132
Fagiolo G. and Dosi G. (2003). Exploitation, exploration and innovation in a model of endogenous growth with locally interacting agents. Structural Change and Economic Dynamics 14: 237–273
Gilbert, N., Pyka, A., & Ahrweiler, P. (2001). Innovation networks-a simulation approach. Journal of Artificial Societies and Social Simulation, 4(3).
Gomes, L. (1998). Ventures column. Wall Street Journal.
Hardie I. and MacKenzie D. (2007). Assembling an economic actor: The agencement of a Hedge Fund. The Sociological Review 55(1): 57–80
Hill, R., Chen, J., Gratch, J., Rosenbloom, P., & Tambe, M. (1997). Intelligent agents for the synthetic battlefield. In: Joint Proceedings of the Fourteenth National Conference on Artificial Intelligence and the Ninth Conference on Innovative Applications of Artificial Intelligence (pp. 1006–1012). Providence, RI, USA.
Himoff, J., Skobelev, P., & Wooldridge, M. (2005). MAGENTA Technology: Multi-agent systems for industrial logistics. In M. Pechoucek, D. Steiner, & S. Thompson (Eds.), Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multi-Agent Systems: Industry Track (pp. 60–66). ACM Press.
IDC. (2005). Worldwide Mobile Phone 2005–2009 Forecast & Analysis Report (Report 33290). International Data Corporation.
Jacobi, S., Madrigal-Mora, C., Leon-Soto, E., & Fischer, K. (2005). Agent steel: An agentbased online system for the planning and observation of steel production. In AAMAS ’05: Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multi-Agent Systems (pp. 114–119) ACM Press: New York, NY, USA.
Krishna V. (2002). Auction theory. Academic Press, San Diego, CA, USA
Levitt T. (1965). Exploit the product life cycle. Harvard Business Review 43(6): 81–94
Lilien G.L., Kotler P. and Moorthy K.S. (1992). Marketing models. Prentice-Hall, Englewood Cliffs, NJ, USA
Luck, M., McBurney, P., Shehory, O., & Willmott, S. (2005). Agent technology: Computing as Interaction. A roadmap for agent based computing. AgentLink III.
Mahajan, V., Muller, E., & Bass, F. M. (1993). New-product diffusion models. In J. Eliashberg & G. L. Lilien (Eds.), Handbooks in operations research and management science, Marketing (Vol. 5, pp. 349–408). Amsterdam: North-Holland.
McKean, J., Shorter, H., McBurney, P., & Luck, M. (2005). The AgentLink III Technology Diffusion Model. Technical Report ULCS-05-008, Department of Computer Science, University of Liverpool, Liverpool, UK.
Midgley D.F. (1977). Innovation and new product marketing. Croom Helm, London
Midgley D.F., Marks R.E. and Kunchamwar D. (2007). Building and assurance of agentbased models: An example and challenge to the field. Journal of Business Research 60(8): 884–893
Moore G.A. (1991). Crossing the chasm: Marketing and selling high-tech products to mainstream consumers. HarperCollins, New York City, NY, USA
Morgan M. (2002). Symposium on Marshall’s Tendencies: 1 How models help economists to know. Economics and Philosophy 18: 5–16
Munroe S., Miller T., Belecheanu R., Pechoucek M., McBurney P. and Luck M. (2006). Crossing the agent technology chasm: Lessons, experiences and challenges in commercial applications of agents. Knowledge Engineering Review 21(4): 345–392
Nicolaisen J., Petrov V. and Tesfatsion L. (2001). Market power and efficiency in a computational electricity market with discriminatory double-auction pricing. IEEE Transactions on Evolutionary Computation 5(5): 504–523
Norman T.J., Preece A., Chalmers S., Jennings N.R., Luck M., Dang V.D., Nguyen T.D., Deora V., Shao J., Gray W.A. and Fiddian N.J. (2004). Agent-based formation of virtual organisations. Knowledge-Based Systems 17: 103–111
Rogers E.M. (1962). Diffusion of innovations. The Free Press, New York City, NY, USA
Rubinstein A. (1998). Modeling bounded rationality. Zeuthen Lecture Book Series. MIT Press, Cambridge, MA, USA
Silverberg G. and Verspagen B (2005). A percolation model of innovation in complex technology spaces. Journal of Economic Dynamics and Control 29(1–2): 225–244
Stroustrup, B. (1985). The C++ Programming Language. Addison Wesley.
Sutton J. (2000). Marshall’s tendencies: What can economists know?. MIT Press, Cambridge, MA, USA
Urban G.L. and Hauser J.R. (1993). Design and marketing of new products. Prentice-Hall, Englewood Cliffs, NJ, USA
Wagner, T., Gasser, L., & Luck, M. (2005). Impact for agents. In M. Pechoucek, D. Steiner, & S. Thompson (Eds.), Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multi-Agent Systems: Industry Track (pp. 93–99). ACM Press.
Weitzel T. (2004). Economics of standards in information networks. Information Age Economy Series. Heidelberg, Physica
Westarp F. (2003). Modeling software markets: Empirical analysis, network simulations and marketing implications. Information Age Economy Series. Physica, Heidelberg
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McKean, J., Shorter, H., Luck, M. et al. Technology diffusion: analysing the diffusion of agent technologies. Auton Agent Multi-Agent Syst 17, 372–396 (2008). https://doi.org/10.1007/s10458-008-9052-y
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DOI: https://doi.org/10.1007/s10458-008-9052-y