Chain: A Dynamic Double Auction Framework for Matching Patient Agents
| Title: | Chain: A Dynamic Double Auction Framework for Matching Patient Agents |
| Author: |
Bredin, Jonathan; Parkes, David C.; Duong, Quang
Note: Order does not necessarily reflect citation order of authors. |
| Citation: | Bredin, Jonathan, David C. Parkes, and Quang Duong. 2007. Chain: A dynamic double auction framework for matching patient agents. Journal of Artificial Intelligence Research 30(1): 133-179. |
| Full Text & Related Files: |
Bredin_Chain.pdf (525.1Kb; PDF) 
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| Abstract: | In this paper we present and evaluate a general framework for the design of truthful auctions for matching agents in a dynamic, two-sided market. A single commodity, such as a resource or a task, is bought and sold by multiple buyers and sellers that arrive and depart over time. Our algorithm, CHAIN, provides the first framework that allows a truthful dynamic double auction (DA) to be constructed from a truthful, single-period (i.e. static) double-auction rule. The pricing and matching method of the CHAIN construction is unique amongst dynamic-auction rules that adopt the same building block. We examine experimentally the allocative efficiency of CHAIN when instantiated on various single-period rules, including the canonical McAfee double-auction rule. For a baseline we also consider non-truthful double auctions populated with "zero-intelligence plus"-style learning agents. CHAIN-based auctions perform well in comparison with other schemes, especially as arrival intensity falls and agent valuations become more volatile. |
| Published Version: | http://portal.acm.org/citation.cfm?id=1622641 |
| Other Sources: | http://www.eecs.harvard.edu/econcs/pubs/bredin07.pdf |
| Terms of Use: | This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA |
| Citable link to this page: | http://nrs.harvard.edu/urn-3:HUL.InstRepos:3967583 |
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