Intelligent Personalized Trading Agents that facilitate Real-time Decision-making for Auctioneers and Buyers in the Dutch Flower Auctions

Wolf Ketter; E van Heck; R Zuidwijk

Intelligent Personalized Trading Agents that facilitate Real-time Decision-making for Auctioneers and Buyers in the Dutch Flower Auctions

Wolf Ketter, E van Heck, R Zuidwijk

Department of Technology and Operations Management

Research output: Book/Report/Inaugural speech/Farewell speech › Report › Academic

Abstract

We propose an evolutionary approach for studying the dynamics of interaction of strategic agents that interact in a marketplace. The goal is to learn which agent strategies are most suited by observing the distribution of the agents that survive in the market over extended periods of time. 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 and co-exist in the same market.

Original language	Undefined/Unknown
Place of Publication	Rotterdam, The Netherlands
Publisher	Rotterdam School of Management (RSM), EUR
Edition	ERIM Report Series Research in Management ERS-2010-016-LIS
Publication status	Published - 2010

Bibliographical note

Babanov-ERIM-WP08

Research programs

RSM LIS

Access to Document

http://hdl.handle.net/1765/115512

Cite this

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title = "Intelligent Personalized Trading Agents that facilitate Real-time Decision-making for Auctioneers and Buyers in the Dutch Flower Auctions",

abstract = "We propose an evolutionary approach for studying the dynamics of interaction of strategic agents that interact in a marketplace. The goal is to learn which agent strategies are most suited by observing the distribution of the agents that survive in the market over extended periods of time. 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 and co-exist in the same market.",

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Intelligent Personalized Trading Agents that facilitate Real-time Decision-making for Auctioneers and Buyers in the Dutch Flower Auctions. / Ketter, Wolf; van Heck, E; Zuidwijk, R.
ERIM Report Series Research in Management ERS-2010-016-LIS ed. Rotterdam, The Netherlands: Rotterdam School of Management (RSM), EUR, 2010.

Research output: Book/Report/Inaugural speech/Farewell speech › Report › Academic

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AU - van Heck, E

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N1 - Babanov-ERIM-WP08

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N2 - We propose an evolutionary approach for studying the dynamics of interaction of strategic agents that interact in a marketplace. The goal is to learn which agent strategies are most suited by observing the distribution of the agents that survive in the market over extended periods of time. 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 and co-exist in the same market.

AB - We propose an evolutionary approach for studying the dynamics of interaction of strategic agents that interact in a marketplace. The goal is to learn which agent strategies are most suited by observing the distribution of the agents that survive in the market over extended periods of time. 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 and co-exist in the same market.

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BT - Intelligent Personalized Trading Agents that facilitate Real-time Decision-making for Auctioneers and Buyers in the Dutch Flower Auctions

PB - Rotterdam School of Management (RSM), EUR

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