Environment orientation: a structured simulation approach for agent-based complex systems

Abstract

Complex systems are collections of independent agents interacting with each other and with their environment to produce emergent behaviour. Agent-based computer simulation is one of the main ways of studying complex systems. A naïve approach to such simulation can fare poorly, due to large communication overhead, and due to the scope for deadlock between the interacting agents sharing a computational platform.Agent interaction can instead be considered entirely from the point of view of the environment(s) within which the agents interact. Structuring a simulation using such Environment Orientation leads to a simulation that reduces communication overhead, that is effectively deadlock-free, and yet still behaves in the manner required. Additionally the Environment Orientation architecture eases the development of more sophisticated large-scale simulations, with multiple kinds of complex agents, situated in and interacting with multiple kinds of environments.We describe the Environment Orientation simulation architecture. We report on a number of experiments that demonstrate the effectiveness of the Environment Orientation approach: a simple flocking system, a flocking system with multiple sensory environments, and a flocking system in an external environment.

CoSMoS special issue editorial

“…Stepney is one of the CoSMoS research team members, and a regular contributor to the workshop series (Garnett et al 2008(Garnett et al , 2010Hoverd and Stepney 2009;Polack et al 2011;Droop et al 2011;Andrews et al 2011Andrews et al , 2012Stepney 2012Stepney , 2013Andrews and Stepney 2014;Afshar Dodson et al 2014 Andrews and Stepney 2014;Ghetiu et al 2009;Read et al 2009). Here he and coauthors extend some of their simulation work to explore how the CoSMoS approach can help clarify and understand the consequences of modelling assumptions.…”

Self-aware architecture to support partial control of emergent behavior

“…A new and decisive role of interactions in describing computing systems was pointed out by R. Milner in [4], and elaborated in [5] and [2]. Indirect interactions, although used widely for describing operation of natural systems (especially those related to modeling swarm intelligence), were introduced to computer science much later as a necessary extension to describe distributed concurrent computations [6,7]. Indirect interactions have obtained more attention in [8,9,10].…”

“…An indirect mediated interaction (i.e. influencing via environment) has turned out to be inevitable to get a realistic simulation of systems with swarm intelligence [7,10].…”

On-line data validation in distributed data fusion

“…An indirect mediated interaction (i.e. influencing via environment) has turned out to be inevitable to get a realistic simulation of systems with swarm intelligence [6,8].…”

“…Complex distributed architectures have been proposed by other sources, such as [8], but oftentimes the proposed solutions are query based. Alternative architectures which rely on service oriented architecture, such as the Intellex system [12], have also been proposed but they fail to address the issues of on-line data validity and quality estimation, either considering these aspects to a limited extent or failing to address the issues completely.…”