Collective behavior is the outcome of a network of local interactions. Here, I consider collective behavior as the result of algorithms that have evolved to operate in response to a particular environment and physiological context. I discuss how algorithms are shaped by the costs of operating under the constraints that the environment imposes, the extent to which the environment is stable, and ...

This article comparatively tests three cooperative co-evolution methods for automated controller design in simulated robot teams. Collective NeuroEvolution (CONE) co-evolves multiple robot controllers using emergent behavioral specialization in order to increase collective behavior task performance. CONE is comparatively evaluated with two related controller design methods in a collective const...

Collective capability of producing patterned collective behaviors is one important field of research in work psychology (e.g., shared cognition approach, Fiore and Salas, 2004; interactive team cognition approach, Cooke et al., 2013), neurosciences (e.g., social neuromarkers, Tognoli et al., in press; neurological mirroring, Waldman et al., 2015), sociology (Miller, 2013), or human movement sci...

W ith the rise of social media, information sharing has been democratized. As a result, users are given opportunities to exhibit different behaviors such as sharing, posting, liking, commenting, and befriending conveniently and on a daily basis. By analyzing behaviors observed on social media, we can categorize these behaviors into individual and collective behavior. Individual behavior is exhi...

This paper analyzes the collective behaviors of swarm robots that play role in the aggregation scenario. Honeybee aggregation is an inspired behavior of young honeybees which tend to aggregate around an optimal zone. This aggregation is implemented based on variation of parameters values. In the second phase, two modifications on original honeybee aggregation namely dynamic velocity and compara...

The emergence of nontrivial collective behavior in networks of coupled chaotic maps is investigated by means of a nonlinear mutual prediction method. The resulting prediction error is used to measure the amount of information that a local unit possesses about the collective dynamics. Applications to locally and globally coupled map systems are considered. The prediction error exhibits phase tra...

This paper describes an ongoing research project in distributed, agent-based manufacturing scheduling systems which exhibit collective system behavior. A scheduling system is described which exhibits purely low-level, reactive behavior. Two types of agents comprise the collective: part agents and machine agents. The collective is a mixedinitiative system in which agents representing parts attem...

When different clients, each with their own individual customization requirements, use the same system simultaneously, the system must dynamically adapt its behavior on a per client basis. Each non-trivial adaptation of the system’s behavior will very likely crosscut the implementation of multiple objects. In this paper we present an extension to the Java programming language that supports the ...

This work quantitatively demonstrates a nontrivial collective behavior, which depends on the coupling strength in chaotic-coupled-map lattices, using the interdependence measure emerging from a local unit. The amount of information flow which flows from the instantaneous mean field to a local map has been investigated using the time-delayed mutual information. Interestingly, the collective syst...

When different clients, each with their own individual customization requirements, use the same system simultaneously, the system must dynamically adapt its behavior on a per client basis. Each non-trivial adaptation of the system’s behavior will very likely crosscut the implementation of multiple objects. In this paper we present an extension to the Java programming language that supports the ...