IAMwildCAT: The Winning Strategy for the TAC Market Design Competition
IAMwildCAT: The Winning Strategy for the TAC Market Design Competition
In this paper we describe the IAMwildCAT agent, designed for the TAC Market Design game which is part of the International Trading Agent Competition. The objective of an agent in this competition is to effectively manage and operate a market that attracts traders to compete for resources in it. This market, in turn, competes against markets operated by other competition entrants and the aim is to maximise the market and profit share of the agent, as well as its transaction success rate. To do this, the agent needs to continually monitor and adapt, in response to the competing marketplaces, the rules it uses to accept offers, clear the market, price the transactions and charge the traders. Given this context, this paper details IAMwildCAT’s strategic behaviour and describes the wide techniques we developed to operationalise this. Finally, we empirically analyse our agent in different environments, including the 2007 competition where it ranked first.
428-432
Vytelingum, Perukrishnen
51f06fc5-024c-450d-bff2-e19c943aa87e
Vetsikas, Ioannis
e6dcc070-9f05-445e-a4f9-1672021c6ef6
Shi, Bing
293fdf16-4597-4ae9-94fd-4415b9b1dc8f
Jennings, Nick
ab3d94cc-247c-4545-9d1e-65873d6cdb30
2008
Vytelingum, Perukrishnen
51f06fc5-024c-450d-bff2-e19c943aa87e
Vetsikas, Ioannis
e6dcc070-9f05-445e-a4f9-1672021c6ef6
Shi, Bing
293fdf16-4597-4ae9-94fd-4415b9b1dc8f
Jennings, Nick
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Vytelingum, Perukrishnen, Vetsikas, Ioannis, Shi, Bing and Jennings, Nick
(2008)
IAMwildCAT: The Winning Strategy for the TAC Market Design Competition.
Proc. 18th European Conf on AI (ECAI), Patras, Greece.
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
In this paper we describe the IAMwildCAT agent, designed for the TAC Market Design game which is part of the International Trading Agent Competition. The objective of an agent in this competition is to effectively manage and operate a market that attracts traders to compete for resources in it. This market, in turn, competes against markets operated by other competition entrants and the aim is to maximise the market and profit share of the agent, as well as its transaction success rate. To do this, the agent needs to continually monitor and adapt, in response to the competing marketplaces, the rules it uses to accept offers, clear the market, price the transactions and charge the traders. Given this context, this paper details IAMwildCAT’s strategic behaviour and describes the wide techniques we developed to operationalise this. Finally, we empirically analyse our agent in different environments, including the 2007 competition where it ranked first.
Text
ecai08-IAMWildCAT.pdf
- Accepted Manuscript
More information
Published date: 2008
Venue - Dates:
Proc. 18th European Conf on AI (ECAI), Patras, Greece, 2008-01-01
Organisations:
Agents, Interactions & Complexity
Identifiers
Local EPrints ID: 265894
URI: http://eprints.soton.ac.uk/id/eprint/265894
PURE UUID: de0c606b-8b30-4027-8bee-861953bd627c
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Date deposited: 11 Jun 2008 07:39
Last modified: 14 Mar 2024 08:16
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Contributors
Author:
Perukrishnen Vytelingum
Author:
Ioannis Vetsikas
Author:
Bing Shi
Author:
Nick Jennings
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