Market-based recommendation: Agents that compete for consumer attention

ABSTRACT

The amount of attention space available for recommending suppliers to consumers on e-commerce sites is typically limited. We present a competitive distributed recommendation mechanism based on adaptive software agents for efficiently allocating the "consumer attention space," or banners. In the example of an electronic shopping mall, the task is delegated to the individual shops, each of which evaluates the information that is available about the consumer and his or her interests (e.g. keywords, product queries, and available parts of a profile). Shops make a monetary bid in an auction where a limited amount of "consumer attention space" for the arriving consumer is sold. Each shop is represented by a software agent that bids for each consumer. This allows shops to rapidly adapt their bidding strategy to focus on consumers interested in their offerings.

For various basic and simple models for on-line consumers, shops, and profiles, we demonstrate the feasibility of our system by evolutionary simulations as in the field of agent-based computational economics (ACE). We also develop adaptive software agents that learn bidding-strategies, based on neural networks and strategy exploration heuristics. Furthermore, we address the commercial and technological advantages of this distributed market-based approach. The mechanism we describe is not limited to the example of the electronic shopping mall, but can easily be extended to other domains.

REFERENCES

• 1: Floortje Alkemade , Han La Poutrè , Hans Amman, Intermediaries in an electronic trade network [Extended Abstract], Proceedings of the 4th ACM conference on Electronic commerce, June 09-12, 2003, San Diego, CA, USA [doi>10.1145/779928.779958]
• 2: Thomas Bäck, Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms, Oxford University Press, Oxford, 1996
• 3: Blattberg, R. and Deighton, J. 1991. Interactive marketing: Exploiting the age of addressability. Sloan Manage. Rev. 33, 5--14.
• 4: Bohte, S. M., Gerding, E., and La Poutré, H. 2001a. Competitive market-based allocation of consumer attention space. Tech. Rep. SEN-R0131, CWI, Amsterdam.
• 5: Sander M. Bohte , Enrico Gerding , Han La Poutré, Competitive market-based allocation of consumer attention space, Proceedings of the 3rd ACM conference on Electronic Commerce, p.202-205, October 14-17, 2001, Tampa, Florida, USA [doi>10.1145/501158.501182]
• 6: Bohte, S. M, Kok, J., and La Poutré, H. 2002. Spike-prop: error-backpropagation in multi-layer networks of spiking neurons. Neurocomputing 48, 1--4 (October), 17--37.
• 7: John Q. Cheng , Michael P. Wellman, The WALRAS Algorithm: A Convergent Distributed Implementation of General Equilibrium Outcomes, Computational Economics, v.12 n.1, p.1-24, August 1998 [doi>10.1023/A:1008654125853]
• 8: Chircu, A. M. and Kauffman, R. J. 1999. Strategies for internet middlemen in the intermediation/disintermediation/reintermediation cycle. Electronic Markets 9, 2, 109--117.
• 9: Clearwater, S., Ed. 1995. Market based Control of Distributed Systems. World Scientific Press, Singapore.
• 10: Dasgupta, P. and Maskin, E. 2000. Efficient auctions. The Quarterly J. Econ. 115, 341--388.
• 11: Gellmann, R. 1996. Disintermediation and the internet. Gov. Info. Quarterly 13, 1, 1--8.
• 12: E. H. Gerding , D. D.B. Bragt , J. A. L Poutre, Multi-issue negotiation processes by evolutionary simulation: validation and social extensions, CWI (Centre for Mathematics and Computer Science), Amsterdam, The Netherlands, 2000
• 13: M. A. Gibney , Nicholas R. Jennings , N. J. Vriend , José-Marie Griffiths, Market-Based Call Routing in Telecommunications Networks Using Adaptive Pricing and Real Bidding, Proceedings of the Third International Workshop on Intelligent Agents for Telecommunication Applications, p.46-61, August 09-10, 1999
• 14: David E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley Longman Publishing Co., Inc., Boston, MA, 1989
• 15: Amy R. Greenwald , Jeffrey O. Kephart, Shopbots and Pricebots, Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, p.506-511, July 31-August 06, 1999
• 16: Robert H. Guttman , Alexandros G. Moukas , Pattie Maes, Agent-mediated electronic commerce: a survey, The Knowledge Engineering Review, v.13 n.2, p.147-159, July 1998 [doi>10.1017/S0269888998002082]
• 17: Haeckel, S. 1998. About the nature and future of interactive marketing. J. Interactive Marketing 12, 63--71.
• 18: Heskes, T. 1997. Practical confidence and prediction intervals. In Advances in Neural Information Processing Systems, M. C. Mozer, M. I. Jordan, and R. Petsche, Eds. Vol. 9. The MIT Press, 176--183.
• 19: John H. Holland, Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence, MIT Press, Cambridge, MA, 1992
• 20: http://www.google.com. Google search engine.
• 21: http://www.overture.com. Overture.
• 22: http://www.worldmall.com. World Mall, online shopping portal.
• 23: Jeffrey O. Kephart , James E. Hanson , Amy R. Greenwald, Dynamic pricing by software agents, Computer Networks: The International Journal of Computer and Telecommunications Networking, v.32 n.6, p.731-752, May 30 2000 [doi>10.1016/S1389-1286(00)00026-8]
• 24: Kirman, A. and Vriend, N. 2001. Evolving market structure: An ACE model of price dispersion and loyalty. J. Dynam. Cont. 25, 459--502.
• 25: Alfred Kobsa, Tailoring Privacy to Users' Needs, Proceedings of the 8th International Conference on User Modeling 2001, p.303-313, July 13-17, 2001
• 26: Krulwich, B. 1996. The BargainFinder agent: Comparison price shopping on the internet. In Agents, Bots and Other Internet Beasties, J. Williams, Ed. SAMS.NET publishing.
• 27: Melanie Mitchell, An introduction to genetic algorithms, MIT Press, Cambridge, MA, 1996
• 28: Alan L. Montgomery, Applying Quantitative Marketing Techniques to the Internet, Interfaces, v.31 n.2, p.90-108, March 2001 [doi>10.1287/inte.31.2.90.10630]
• 29: Montgomery, A. and Srinivasan, K. 2002. Learning about customers without asking. In The Power of One-Leverage Value from Personalization Technologies, N. Pal and A. Rangaswamy, Eds. eBRC Press, Penn State University.
• 30: Moreau, L., Zaini, N., Zhou, J., Jennings, N. R., Wei, Y. Z., Hall, W., de Roure, D., Gilchrist, I., ODell, M., Reich, S., Berka, T., and di Napoli, C. 2002. A market-based recommender system. In Proceedings of the 4th International Workshop on Agent-Oriented Information Systems, Bologna, Italy. 50--67.
• 31: Moukas, A., Guttman, R., and Maes, P. 1998. Agent-mediated Electronic Commerce: An MIT Media Laboratory Perspective. In Proceedings of the International Conference on Electronic Commerce, Seoul, Korea.
• 32: Nissen, M. 2000. Agent-based supply chain disintermediation versus re-intermeditation: Economic and technological perspectives. Int. J. Intell. Syst. Accounting, Finance and Management 9, 237--256.
• 33: Hyacinth S. Nwana , Divine T. Ndumu, A perspective on software agents research, The Knowledge Engineering Review, v.14 n.2, p.125-142, September 1999 [doi>10.1017/S0269888999142012]
• 34: M. J. Owen , L. Lee , G. Sewell , S. Steward , D. Thomas, Multi-agent Trading Environment, BT Technology Journal, v.17 n.3, p.33-43, July 1999 [doi>10.1023/A:1009668118167]
• 35: Peppers, D., Rogers, M., and Dorf, B. 1999. Is your company ready for one-to-one marketing? Harvard Bus. Rev. 77, 151--162.
• 36: J. Ben Schafer , Joseph Konstan , John Riedi, Recommender systems in e-commerce, Proceedings of the 1st ACM conference on Electronic commerce, p.158-166, November 03-05, 1999, Denver, Colorado, United States [doi>10.1145/336992.337035]
• 37: Greg Shaffer , Z. John Zhang, Competitive One-to-One Promotions, Management Science, v.48 n.9, p.1143-1160, September 2002 [doi>10.1287/mnsc.48.9.1143.172]
• 38: Richard S. Sutton , Andrew G. Barto, Introduction to Reinforcement Learning, MIT Press, Cambridge, MA, 1998
• 39: Pieter Jan't Hoen , Sander Bohte , Enrico Gerding , Han La Poutré, An Extensible Agent Architecture for a Competitive Market-Based Allocation of Consumer Attention Space, Revised Papers from the Workshop on Agent Mediated Electronic Commerce on Agent-Mediated Electronic Commerce IV, Designing Mechanisms and Systems, p.273-288, July 16, 2002
• 40: Tesfatsion, L. 2001. Introduction to the special issue on agent-based computational economics. J. Econom. Dynam. Cont. 25, 3/4, 281--293.
• 41: D. D.B. Bragt , E. H. Gerding , J. A. L Poutre, Equilibrium selection in alternating-offers bargaining models -- the evolutionary computing approach, CWI (Centre for Mathematics and Computer Science), Amsterdam, The Netherlands, 2000
• 42: Van Bragt, D. and La Poutré, H. 2001. Generating efficient automata for negotiations---an exploration with evolutionary algorithms. In Proceedings of the Genetic and Evolutionary Computation Conference (GECKO-2001), San Francisco, July 2001.
• 43: David Van Bragt , Cees Van Kemenade , Han La Poutré, The Influence of Evolutionary Selection Schemes on the Iterated Prisoner's Dilemma, Computational Economics, v.17 n.2-3, p.253-263, June 2001 [doi>10.1023/A:1011657018442]
• 44: Varian, H. 1995. Economic mechanism design for computerized agents. In First USENIX Workshop on Electronic Commerce. New York, 13--21.
• 45: Vermeer, B. 2001. Data Quality and Data Alignment in E-Business. Ph.D. thesis, Eindhoven University of Technology.
• 46: Vickrey, W. 1961. Counterspeculation, auctions and competitive sealed tenders. J. Finance 16, 8--37.
• 47: Nicolaas J. Vriend, Self-organization of markets: an example of a computational approach, Computational Economics, v.8 n.3, p.205-231, Aug. 1995 [doi>10.1007/BF01298460]
• 48: Gerhard Weiss, Multiagent systems: a modern approach to distributed artificial intelligence, MIT Press, Cambridge, MA, 1999

INDEX TERMS

Primary Classification:
  C. Computer Systems Organization
  C.2 COMPUTER-COMMUNICATION NETWORKS
      C.2.4 Distributed Systems
          Subjects: Distributed applications

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
        I.2.11 Distributed Artificial Intelligence
            Subjects: Languages and structures
      I.2.6 Learning
          Subjects: Connectionism and neural nets

  J. Computer Applications
  J.4 SOCIAL AND BEHAVIORAL SCIENCES

  K. Computing Milieux
  K.4 COMPUTERS AND SOCIETY
      K.4.4 Electronic Commerce
          Subjects: Distributed commercial transactions

General Terms:
Algorithms, Economics

Keywords:
ACE, agent-based computational economics, competitive multi-agent systems, electronic markets, learning agents, market-based programming, recommendation systems