An Empirical Approach to a Theory of Coordination. Part I: Design Principles and First Results

Coordination is understood to consist of a set of mechanisms necessary for the effective operation of Intelligent Agent Societies (IASs). In building such societies, it is important to design and implement coordination in accordance with the known requirements and anticipated working conditions of the IAS in question. Currently, there is little theoretical support that could help in this process. We outline the approach and design principles of our work on automatically generating an empirically-based theory of coordination. We also describe the first set of results obtained, which prove the feasibility of the approach.We are concerned with Distributed Problem Solving (DPS) systems in which all agents share an identical goal structure and fully collaborate, as opposed to Multi-Agent Systems (MAS) in which agents may also compete with one another. Our investigation is based on an easily modifiable and parametrizable generic IAS, the P-system, a metaphorical and abstract version of our earlier work, the Distributed Control of Nationwide Manufacturing Operations. The P-system shares characteristic properties with most, if not all, IASs. It was used for a sequence of rigorously designed experiments in which control variables operated under well-defined conditions and performance measures were observed. We infer, from the statistical analysis of these data, characteristic and important descriptors of the organization and functioning of IASs in general. The resulting relations should produce insight into the fundamental issues of coordination, provide design tools and guidelines for the construction of new IASs, and lend support in trouble-shooting existing ones.