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

TY - JOUR

T1 - Environment Orientation

T2 - a structured simulation approach for agent-based complex systems

AU - Hoverd, Tim

AU - Stepney, Susan

N1 - (c) Springer Science+Business Media Dordrecht 2014. This is an author produced version of a paper published in Natural Computing. Uploaded in accordance with the publisher's self-archiving policy.

PY - 2015/3

Y1 - 2015/3

N2 - 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 naive 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.

AB - 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 naive 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.

U2 - 10.1007/s11047-014-9449-2

DO - 10.1007/s11047-014-9449-2

M3 - Article

SN - 1567-7818

VL - 14

SP - 83

EP - 97

JO - Natural Computing

JF - Natural Computing

IS - 1

ER -