Modeling and Analysis of the Collective Dynamics of Large-Scale Multi-Agent Systems: A Cellular and Network Automata based Approach∗

This technical report addresses a particular approach to modeling and analysis of the behavior of large-scale multi-agent systems. A broad variety of multi-agent systems are modeled as appropriate variants of cellular and network automata. Several fundamental properties of the collective dynamics of those cellular and network automata are then formally analyzed. Various loosely coupled large-scale distributed information systems are of an increasing interest in a variety of areas of computer science and its applications – areas as diverse as team robotics, intelligent transportation systems, open distributed software environments, disaster response management, distributed databases and information retrieval, and computational theories of language evolution. A popular paradigm for abstracting such distributed infrastructures is that of multi-agent systems (MAS) made of typically a large number of autonomous agents that locally interact with each other. This report is an attempt at a cellular and network automata based mathematical and computational theory of such MAS. The emphasis of this report is placed on the following three important aspects of largescale multi-agent systems. First, the temporal and causal nature of inter-agent interactions is addressed, and some of its consequences discussed. In that context, a comparison and contrast of cellular automata with different communication models is undertaken. Second, the implications of homogeneity vs. heterogeneity of the individual agent behaviors in a large-scale MAS are analyzed. Third, in conjunction with the models of individual agent behaviors, the impact of the communication network topology on the collective behavior of large agent ensembles is studied. In particular, it is formally established that a number of fundamental problems about the collective dynamics of large-scale MAS are demonstrably computationally intractable. Moreover, that intractability is shown to hold even when instances of the network automata models of multi-agent systems under scrutiny are severely constrained. Research summarized in this report strengthens and/or generalizes much of the previous work on the global behavior of various models of discrete dynamical systems studied in the literature, such as the classical cellular automata and discrete Hopfield networks. Among several far-reaching implications of the results presented herein, perhaps the most important is the general conclusion that a highly complex and unpredictable collective dynamics in multiagent systems can often arise from a synergy of very simple individual agent behaviors and their loosely coupled local interactions.