Two-Sided Learning in an Agent Economy for Information Bundles

Commerce 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 o ered in widely varying con gurations. 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 nd 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 su ciently 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.