Abstract: Following the view point of Evolutionary Dynamics, we have built a
multi-agent system to study resource allocation in a heterogeneous network of
resources. The class of systems we are looking at are systems facing structural
uncertainties (supply structure and growth, concentration level, substitute
products, ...). In our approach [1,2] resources are modeled as strategies, and
agents distribute processing requirements onto resources using imperfect
information and local decision making. Our agents are endowed with bounded
rationality [8] and have to face the challenge of dealing with imperfect
understanding of the feedback structure from resources which use unintendedly
rational heuristics to set resources' unit prices. Our intent is to achieve
cooperative equilibrium using competitive dynamics by controlling congestion
through capacity pricing. To achieve this, a distributed differentiated pricing
scheme has been used to improve loose coupling between agents and resources.
The dynamics of this pricing scheme has been studied in [3]. This required a
loosely coupled interaction model that adequately reflects the autonomy of the
involved parties and provides the necessary spatial and temporal decoupling
[4]. However, the benefits of greater decentralization and increased local
decision-making come at the expense of greater stochastic dynamics which can
have unpredictable effects on the stability of the system. Because such
non-functional properties (stability, performance, etc) depend upon the
system's underlying design and implementation [5], we had to come up with an
appropriate approach for its stability analysis. This paper first describes the
system under study. Following, we describe the procedure we use to analyze its
stability and then show its concrete application.