The origins of large-scale spatial patterns in biology have been an important source of theoretical speculation since the pioneering work by Turing (1952) on the chemical basis of morphogenesis. Knowing how these patterns emerge and their functional role is important to our understanding of the evolution of biocomplexity and the role played by self organization. However, so far, conclusive evidence for local activation-long-range inhibition mechanisms in real biological systems has been elusive. Here a welldefined experimental and theoretical analysis of the pattern formation dynamics exhibited by clustering behavior in ant colonies is presented. These experiments and a simple mathematical model show that these colonies do indeed use this type of mechanism. All microscopic variables have been measured and provide the first evidence, to our knowledge, for this type of self-organized behavior in complex biological systems, supporting early conjectures about its role in the organization of insect societies.M any biological systems display large-scale features involving some characteristic scale that is much larger than the size of its individual components (1). These structures are observed in a broad range of systems and scales, from animal coats (2), shell patterns (3, 4), and neural structures (5) to the spatial distribution of individuals in ecosystems (6). In many cases, they reflect functionality and adaptation and in all of them, they provide clues for the underlying rules that generate them. In most cases, it is clear that the information available to individual units is gathered from a local neighborhood much smaller than the resulting structures, suggesting some type of amplification mechanism that relies on collective behavior.The first theoretical explanation of these types of structures was suggested in 1952 by Alan Turing (1,7,8). The basic mechanism at work involves local amplification of fluctuations (activation) and long-range inhibition and actually falls within a general class of mechanisms (9-12). These mechanisms have been identified in physical (13) and chemical (14) systems, in ecosystems (2, 6, 10, 15-18) and morphogenesis (2-5, 11, 19-26). In the slime mold (27, 28), the evidence is also strong. Critics have argued that a proof requires the identification and measurement of the microscopic mechanisms at work, and this is obviously a rather difficult task in biology.In this context, it was early suggested that social insects might actually use these types of mechanisms to build their nests (29,30) and produce a wide variety of spatiotemporal structures (31-34). Here we use social insects and their behavioral patterns of organization as our reference system. We follow a standard approach, using a well-defined and controlled experimental setup in which the whole set of parameters can be measured and therefore all of the microscopic rules can be identified. We show that the formation of cemeteries in ants (35-38) falls within the family of local activation-long range inhibition (LALI) processes...

We report the faithful reproduction of the self-organized aggregation behavior of the German cockroach Blattella germanica with a group of robots. We describe the implementation of the biological model provided by Jeanson et al. in Alice robots, and we compare the behaviors of the cockroaches and the robots using the same experimental and analytical methodology. We show that the aggregation behavior of the German cockroach was successfully transferred to the Alice robot despite strong differences between robots and animals at the perceptual, actuatorial, and computational levels. This article highlights some of the major constraints one may encounter during such a work and proposes general principles to ensure that the behavioral model is accurately transferred to the artificial agents.