Chain: A Dynamic Double Auction Framework for Matching Patient Agents

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.

ICE: An Expressive Iterative Combinatorial Exchange

“…The other two major directions for future work are to: (a) modify the design to allow bidders to refine the structure, not just the valuation bounds on their TBBL tree, across rounds; (b) extend ICE to work in a dynamic environment with a changing bidder population, for instance maintaining linear price feedback and periodically clearing. Recent progress in on-line mechanism design includes truthful, dynamic double auctions for very simple expressiveness (Blum, Sandholm, & Zinkevich, 2006;Bredin, Parkes, & Duong, 2007), but does not extend to the kind of expressiveness and price sophistication present in ICE; see the work of Parkes (2007) for a recent survey. Lastly, the incentive properties of ICE are very much dependent on the payment rule used which argues for further analysis of the Threshold rule and its alternatives.…”

Incremental Design of Perishable Goods Markets through Multi-Agent Simulations

“…As a preliminary study for an online DA, an efficient and truthful mechanism for a static DA with temporally constrained bids was developed using weighted bipartite matching in graph theory [13]. In addition, for online DAs, some studies have addressed several important aspects of the mechanism, such as design of matching algorithms with good worst-case performance within the competitive analysis framework [14], construction of a general framework that facilitates a truthful dynamic DA by extending static DA rules [15], and an application to electric vehicle charging problems [16]. Although these research results are innovative and significant, we cannot directly apply their mechanisms to our online DA problem because their models incorporate the assumption that trade failures never cause a loss to traders, which is not true in perishable goods markets.…”

Design of online double auction mechanism for aging sensitive commodity

“…After that, Bredin, Zhao, and Laurent etc., designed a variety of matching and payment algorithm for online double auction mechanism. So far, online auction mechanism has been preliminarily studied in many fields such as electric vehicle charging of the network background, wireless spectrum auction, cloud resource allocation and so on [3] [32] [33].…”