Show simple item record

Two-sided Learning in an Agent Economy for Information Bundles

dc.contributor.authorKephart, Jeffrey O.
dc.contributor.authorDas, Rajarshi
dc.contributor.authorMacKie-Mason, Jeffrey K.
dc.date.accessioned2007-04-11T02:55:57Z
dc.date.available2007-04-11T02:55:57Z
dc.date.issued2000
dc.identifier.citationin Agent-mediated Electronic Commerce, Lecture Notes in Artificial Intelligence. Berlin: Springer-Verlag, 2000. <http://hdl.handle.net/2027.42/50446>en
dc.identifier.urihttps://hdl.handle.net/2027.42/50446
dc.description.abstractCommerce in information goods is one of the earliest emerging applications for intelligent agents in commerce. However, the fundamental characteristics of information goods mean that they can and likely will be offered in widely varying configurations. Participating agents will need to deal with uncertainty about both prices and location in multi-dimensional product space. Thus, studying the behavior of learning agents is central to understanding and designing for agent-based information economies. Since uncertainty will exist on both sides of transactions, and interactions between learning agents that are negotiating and transacting with other learning agents may lead to unexpected dynamics, it is important to study two-sided learning. We present a simple but powerful model of an information bundling economy with a single producer and multiple consumer agents. We explore the pricing and purchasing behavior of these agents when articles can be bundled. In this initial exploration, we study the dynamics of this economy when consumer agents are uninformed about the distribution of article values. We discover that a reasonable albeit naive consumer learning strategy can lead to disastrous market behavior. We find a simple explanation for this market failure, and develop a simple improvement to the producer agent's strategy that largely ameliorates the problem. But in the process we learn an important lesson: dynamic market interactions when there is substantial uncertainty can lead to pathological outcomes if agents are designed with "reasonable" but not sufficiently adaptive strategies. Thus, in programmed agent environments it may be essential to dramatically increase our understanding of adaptivity and learning if we want to obtain good aggregate outcomes.en
dc.format.extent381293 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_USen
dc.titleTwo-sided Learning in an Agent Economy for Information Bundlesen
dc.typeArticleen_US
dc.subject.hlbsecondlevelInformation and Library Science
dc.subject.hlbtoplevelSocial Sciences
dc.contributor.affiliationumInformation, School ofen
dc.contributor.affiliationumcampusAnn Arboren
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/50446/1/bundle.pdfen_US
dc.owningcollnameInformation, School of (SI)


Files in this item

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.