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Multiattribute Call Markets.
Lochner, Kevin M.
Lochner, Kevin M.
2008
Abstract: Multiattribute auctions support automated negotiation in
settings where buyers and sellers have valuations for alternate
configurations of a good, as defined by configuration
attributes. Bidders express offers to buy or sell alternate
configurations by specifying configuration-dependent reserve prices,
and the auction determines both the traded goods and transaction
prices based on these offers.
While multiattribute auctions have been deployed in single-buyer
procurement settings, the development of double-sided multiattribute
auctions-allowing the free participation of both buyers and
sellers-has received little attention from academia or industry.
In this work I develop a multiattribute call market, a
specific type of double auction in which bids accumulate over an
extended period of time, before the auction determines trades based
on the aggregate collection of bids. Building on a polynomial-time
clearing algorithm, I contribute an efficient algorithm for
information feedback. Supporting the implementation of market-based
algorithms, information feedback support extends the range of
settings for which multiattribute call markets achieve efficiency.
Multiattribute auctions are only one of many auction variants
introduced in recent years. The rapidly growing space of
alternative auctions and trading scenarios calls for both a
standardized language with which to specify auctions, as well as a
computational test environment in which to evaluate alternate
designs. I present a novel auction description language and
deployment environment that supports the specification of a broad
class of auctions, improving on prior approaches through a scripting
language that employs both static parameter settings and rule-based
behavior invocation. The market game platform, AB3D, can
execute these auction scripts to implement multi-auction and
multi-agent trading scenarios.
The efficiency of multiattribute call markets depends crucially on
the underlying valuations of participants. I analyze the expected
performance limitations of multiattribute call markets, using
existing analytical results where applicable. Addressing a lack of
theoretical guidance in many natural settings, I introduce a
computational metric on bidder valuations, and show a correlation
between this metric and the expected efficiency of multiattribute
call markets. As further validation, I integrate multiattribute
markets into an existing supply chain simulation, demonstrating
efficiency gains over a more conventional negotiation procedure.