Emergent service provisioning and demand estimation through self-organizing agent communities

A major challenge within open markets is the ability to satisfy service demand with an adequate supply of service providers, especially when such demand may be volatile due to changing requirements, or fluctuations in the availability of services. Ideally, this supply and demand should be balanced; however, when consumer demand changes over time, and providers independently choose which services they provide, a coordination problem known as ‘herding’ can arise bringing instability to the market. This behavior can emerge when consumers share similar preferences for the same providers, and thus compete for the same resources. Likewise, providers which share estimates of fluctuating demand may respond in unison, withdrawing some services to introduce others, and thus oscillate the available supply around some ideal equilibrium. One approach to avoid this unstable behavior is to limit the flow of information between agents, such that they possess an incomplete and subjective view of the local service availability.We propose a model of an adaptive service-offering mechanism, in which providers adapt their choice of services offered to consumers, based on perceived demand. By varying the volume of information shared by agents, we demonstrate that a co-adaptive equilibrium can be achieved, thus avoiding the herding problem. As the knowledge that agents possess is limited, they self-organise into community structures that support locally shared information. We demonstrate that such a model is capable of reducing instability in service demand and thus increase utility (based on successful service provision) by up to 59%, when compared to the use of globally available information.