Abstract
We study the price dynamics in a multi-agent economy consisting of buyers and competing sellers, where each seller has limited information about its competitors’ prices. In this economy, buyers use shopbots while the sellers employ automated pricing agents or pricebots. A pricebot resets its seller’s price at regular intervals with the objective of maximizing revenue in each time period. Derivative following provides a simple, albeit naive, strategy for dynamic pricing in such a scenario. In this paper, we refine the derivative following algorithm and introduce a model-optimizer algorithm that re-estimates the price-profit relationship for a seller in each period more efficiently. Simulations using the model-optimizer algorithm indicate that it outperforms derivative following even though it does not have any additional information about the market. Our results underscore the role machine learning and optimization can play in fostering competition (or cooperation) in a multi-agent economy where the agents have limited information about their environment.
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
Brooks, C.H., Durfee, E.H., Das, R.: Price wars and niche discovery in an information economy (2000) (in preparation)
Brooks, C.H., Fay, S., Das, R., Mackie-Mason, J.K., Kephart, J.O., Durfee, E.H.: Automated search strategies in an electronic goods market: Learning and complex price scheduling. In: Proceedings of the ACM Conference on Electronic Commerce (1999)
Clark, D.: Shopbots become agents for business change. IEEE Computer 33, 18–21 (2000)
Dasgupta, P., Das, R.: Dynamic service pricing for brokers in a multi-agent economy. In: Proceedings of the Fourth International Conference on Multi-agent systems, July 2000. Springer, Heidelberg (2000)
Greenwald, A.R., Kephart, J.O.: Shopbots and pricebots. In: Lecture Notes on Artificial Intelligence: Proceedings of the IJCAI Workshop on Agent-mediated Electronic Commerce. Springer, Heidelberg (2000)
Greenwald, A.R., Kephart, J.O., Tesauro, G.J.: Strategic pricebot dynamics. In: Proceedings of 1st ACM Conference on E-Commerce (1999)
Kephart, J.O., Das, R., Mackie-Mason, J.K.: Two-sided learning in an agent economy for information bundles. In: Lecture Notes on Artificial Intelligence: Proceedings of the IJCAI Workshop on Agent-mediated Electronic Commerce. Springer, Heidelberg (2000)
Kephart, J.O., Greenwald, A.R.: Shopbot economics. In: Proceedings of Fifth European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (1999)
Kephart, J.O., Hanson, J.E., Greenwald, A.R.: Dynamic pricing by software agents. To appear in Computer Networks (2000)
Nelder, J.A., Mead, R.: A simplex method for function minimization. Computer Journal 7, 308–313 (1965)
Press, W.H., Flannery, B.P., Teukolsky, S.A., Vetterling, W.T.: Numerical Recipes in C: The Art of Scientific Computing. Cambridge University Press, Cambridge (1988)
Tesauro, G.J., Kephart, J.O.: Pricing in agent economies using multi-agent q-learning. In: Proceedings of Fifth European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (1999)
Tseng, P.: Fortified-descent simplical search method: a general approach. Department of Mathematics, University of Washington, Seattle (1998)
Varian, H.R.: Market structure in the network age. In: Proceedings of Understanding the Digital Economy Conference, Department of Commerce, Washington, DC, USA (May 1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Dasgupta, P., Das, R. (2000). Dynamic Pricing with Limited Competitor Information in a Multi-Agent Economy. In: Scheuermann, P., Etzion, O. (eds) Cooperative Information Systems. CoopIS 2000. Lecture Notes in Computer Science, vol 1901. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10722620_28
Download citation
DOI: https://doi.org/10.1007/10722620_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-41021-8
Online ISBN: 978-3-540-45266-9
eBook Packages: Springer Book Archive