Chain: A Dynamic Double Auction Framework for Matching Patient Agents

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 a...

• Type: Journal
• Year: 2007
• Where: JAIR
• Authors: Jonathan Bredin, David C. Parkes, Quang Duong
• Keywords: Auctions, Double Auctions, JAIR 2007, Truthful