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DOI: http://dx.doi.org/10.7551/978-0-262-31709-2-ch143
Pages 957-964
First published 2 September 2013

Artificial Reaction Network Agents

Claire E. Gerrard, John McCall, George Coghill, Christopher Macleod

Abstract

The Artificial Reaction Network (ARN) is an Artificial Chemistry representation inspired by cell signaling networks. The ARN has previously been applied to the simulation of biological signaling pathways and to the control of limbed robots. In this paper we create multiple cell-like autonomous agents using ARN networks. It is shown that these agents can simulate some aspects of the behavior of biological amoebae. To demonstrate practical applications of such agents they are then reconfigured as a swarm of robots in a simulated oil spill clean-up operation. We demonstrate that ARN agents, like amoebae, can autonomously recognize environmental patterns and produce emergent behavior. The results show that such agents may be useful in biological simulation and furthermore may have practical applications in swarm robotics.