A diversity dilemma in evolutionary markets

Peter R. Lewis*, Paul Marrow, Xin Yao

*Corresponding author for this work

Research output: Chapter in Book/Published conference outputConference publication


Markets are useful mechanisms for performing resource al- location in fully decentralised computational and other systems, since they can possess a range of desirable properties, such as efficiency, decentralisation, robustness and scalability. In this paper we investigate the behaviour of co-evolving evolutionary market agents as adaptive offer generators for sellers in a multi-attribute posted-offer market. We demonstrate that the evolutionary approach enables sellers to automatically position themselves in market niches, created by heterogeneous buyers. We find that a trade-off exists for the evolutionary sellers between maintaining high population diversity to facilitate movement between niches and low diversity to exploit the current niche and maximise cumulative payoff. We characterise the trade-off from the perspective of the system as a whole, and subsequently from that of an individual seller. Our results highlight a decision on risk aversion for resource providers, but crucially we show that rational self-interested sellers would not adopt the behaviour likely to lead to the ideal result from the system point of view.

Original languageEnglish
Title of host publicationICEC '11
Subtitle of host publicationproceedings of the 13th International Conference on Electronic Commerce
Place of PublicationNew York, NY (US)
Number of pages10
ISBN (Print)978-1-4503-1428-2
Publication statusPublished - 1 Dec 2011
Event13th International Conference on Electronic Commerce - Liverpool, United Kingdom
Duration: 3 Aug 20115 Aug 2011

Publication series

NameACM international conference proceeding series


Conference13th International Conference on Electronic Commerce
Abbreviated titleICEC'11
Country/TerritoryUnited Kingdom


  • co-evolution
  • diversity
  • market-based control
  • online evolution
  • self-interested agents


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