First steps on asynchronous lattice-gas models with an application to a swarming rule

International audienceLattice-gas cellular automata are often considered as a particular case of cellular automata in which additional constraints apply, such as conservation of particles or spatial exclusion. But what about their updating? How to deal with non-perfect synchrony? Novel definitions of asynchronism are proposed that respect the specific hypotheses of lattice-gas models. These definitions are then applied to a swarming rule in order to explore the robustness of the global emergent behaviour. In particular, we compare the synchronous and asynchronous case, and remark that anti-alignment of particles is no longer observed when a small critical amount of asynchronism is added

Emergence of Macro Spatial Structures in Dissipative Cellular Automata

This paper describes the peculiar behavior observed in a class of cellular automata that we have defined as dissipative, i.e., cellular automata that are open and makes it possible for the environment to influence their evolution. Peculiar in the dynamic evolution of this class of cellular automata is that stable macro-level spatial structures emerge from local interactions among cells, a behavior that does not emerge when the cellular automaton is closed, i.e., when the state of a cell is not influenced by the external world. Moreover, we observed that Dissipative Cellular Automata (DCA) exhibit a behavior very similar to that of dissipative structures, as macro-level spatial structures emerge as soon as the external perturbation exceeds a threshold value and it stays below the "turbulence" limit. Finally, we discuss possible relations of the performed experiments with the area of open distributed computing, and in particular of agent-based distributed computing

Searching for pattern-forming asynchronous cellular automata – An evolutionary approach

Abstract. This paper discusses a class of 2-dimensional asynchronous cellular automata with conservation of mass, for the formation of patterns in groups. The previous study reported a methodology of searching, automatically, for pattern-forming cellular automata using a genetic algorithm; this approach successfully found a few types of pattern-forming rules. The current study is a series of statistical analyses of one of the classes found by the above methodology, with the hope of understanding the mechanisms of the pattern formation. These analyses lead to some basic logic necessary to the pattern formation, but not to enough information to elucidate the whole mechanism of the pattern formation. This result suggests that the existence of unidentified cooperative operations between the different transitions of the cellular automaton rule to carry out the pattern formation.

On Modeling and Analyzing Sparsely Networked Large-Scale Multi-agent Systems with Cellular and Graph Automata

Modeling, designing and analyzing large scale multi-agent systems (MAS) with anywhere from tens of thousands to millions of autonomous agents will require mathematical and computational theories and models substantially different from those underlying the study of small- to medium-scale MAS made of only dozens, or perhaps hundreds, of agents. In this paper, we study certain aspects of the global behavior of large ensembles of simple reactive agents. We do so by analyzing the collective dynamics of several related models of discrete complex systems based on cellular automata. We survey our recent results on dynamical properties of the complex systems of interest, and discuss some useful ways forward in modeling and analysis of large-scale MAS via appropriately modified versions of the classical cellular automata