Abstract
We propose an evolutionary approach for studying strategic agents that interact in electronic marketplaces. We describe how this approach can be used when agents’ strategies are based on different methodologies, employing incompatible rules for collecting information and for reproduction. We present experimental results from a simulated market, where multiple service providers compete for customers using different deployment and pricing schemes. The results show that heterogeneous strategies evolve in the same market and provide useful research data.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Anas, A., Arnott, R., Small, K.A.: Urban spatial structure. Journal of Economic Literature 36(3), 1426–1464 (1998)
Axelrod, R.M.: The evolution of cooperation. Basic Books, New York (1984)
Axelrod, R.: The complexity of cooperation. Princeton University Press, Princeton (1997)
Babanov, A., Ketter, W., Gini, M.: An evolutionary framework for large-scale experimentation in multi-agent systems. In: Wagner, T. (ed.) MAS Problem Spaces and Their Implications to Achieving Globally Coherent Behavior, Kluwer, Dordrecht (2003)
Brooks, C.H., Gazzale, R., Das, R., Kephart, J.O., MacKie-Mason, J.K., Durfee, E.H.: Model selection in an information economy: Choosing what to learn. Computational Intelligence (April 2002)
Cliff, D., Bruten, J.: Minimal intelligence agents for bargaining behaviors in marketbased environments. Technical Report HPL-97-91, Hewlett Packard Labs (1997)
Cliff, D.: Evolutionary optimization of parameter sets for adaptive softwareagent traders in continuous double auction markets. Technical Report HPL-2001-99, Hewlett Packard Labs (2001)
Collins, J., Ketter, W., Gini, M.: A multi-agent negotiation testbed for contracting tasks with temporal and precedence constraints. Int’l Journal of Electronic Commerce 7(1), 35–57 (2002)
Das, R., Hanson, J.E., Kephart, J.O., Tesauro, G.: Agenthuman interactions in the continuous double auction. In: Proc. of the 17th Joint Conf. on Artificial Intelligence, Seattle, WA, USA (August 2001)
DiMicco, J.M., Greenwald, A., Maes, P.: Dynamic pricing strategies under a finite time horizon. In: Proc. of ACM Conf. on Electronic Commerce (EC 2001) (October 2001)
Epstein, J.M., Axtell, R.: Growing Artificial Societies: Social Science from the Bottom Up. The MIT Press, Cambridge (1996)
Forrest, S.: Genetic algorithms: Principles of natural selection applied to computation. Science 261, 872–878 (1993)
Gaylord, R.J., D’Andrea, L.J.: Simulating Society. Springer, Heidelberg (1998)
Kephart, J.O., Hanson, J.E., Greenwald, A.R.: Dynamic pricing by software agents. Computer Networks 32(6), 731–752 (2000)
Lerman, K.: Design and mathematical analysis of agent-based systems. In: Rash, J.L., Rouff, C.A., Truszkowski, W., Gordon, D.F., Hinchey, M.G. (eds.) FAABS 2000. LNCS (LNAI), vol. 1871, pp. 222–233. Springer, Heidelberg (2001)
Lindgren, K.: Evolutionary dynamics in game-theoretic models. In: The Economy as an Evolving Complex System II, pp. 337–367 (1997)
McFadzean, D., Stewart, D., Tesfatsion, L.: A computational laboratory for evolutionary trade networks. IEEE Transactions on Evolutionary Computation 5(5), 546–560 (2001)
Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs. Springer, Heidelberg (1996)
Mills, E.S., Lav, M.R.: A model of market areas with free entry. Journal of Political Economy 72(3), 278–288 (1964)
Nelson, R.R.: Recent evolutionary theorizing about economic change. Journal of Economic Literature 33(1), 48–90 (1995)
Oechssler, J., Riedel, F.: On the dynamic foundation of evolutionary stability in continuous models. Journal of Economic Theory 107, 223–252 (2002)
O’Sullivan, A.: Urban Economics. McGraw-Hill Higher Education (1999)
Park, S., Durfee, E.H., Birmingham, W.P.: An adaptive agent bidding strategy based on stochastic modeling. In: Proc. of the Third Int’l Conf. on Autonomous Agents (1999)
Phelps, S., McBurney, P., Parsons, S., Sklar, E.: Coevolutionary mechanism design: a preliminary report. In: Padget, J., Shehory, O., Parkes, D.C., Sadeh, N.M., Walsh, W.E. (eds.) AMEC 2002. LNCS (LNAI), vol. 2531, pp. 123–142. Springer, Heidelberg (2002)
Roth, A.E.: The economist as engineer: Game theory, experimentation, and computation as tools for design economics. Econometrica 70(4), 1341–1378 (2002)
Schelling, T.C.: Micromotives and Macrobehavior. W.W. Norton & Company, Inc., New York (1978)
Shehory, O., Kraus, S., Yadgar, O.: Emergent cooperative goal-satisfaction in large scale automated-agent systems. Artificial Intelligence 110(1) (May 1999)
Maynard Smith, J.: Evolution and the Theory of Games, December 1982. Cambridge University Press, Cambridge (1982)
Tesfatsion, L.: Agent-based computational economics: Growing economies from the bottom up. Artificial Life 8(1), 55–82 (2002)
Weibull, J.W.: Evolutionary Game Theory. The MIT Press, Cambridge (1995)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Babanov, A., Ketter, W., Gini, M. (2004). An Evolutionary Approach for Studying Heterogeneous Strategies in Electronic Markets. In: Di Marzo Serugendo, G., Karageorgos, A., Rana, O.F., Zambonelli, F. (eds) Engineering Self-Organising Systems. ESOA 2003. Lecture Notes in Computer Science(), vol 2977. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24701-2_11
Download citation
DOI: https://doi.org/10.1007/978-3-540-24701-2_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-21201-0
Online ISBN: 978-3-540-24701-2
eBook Packages: Springer Book Archive