Quantifi cation and Analysis of the Resilience of Two Swarm Intelligent Algorithms

Joshua Cherian Varughese, Ronald Thenius, Thomas Schmickl, Franz Wotawa
in 3rd Global Conference on Artificial Intelligence, EPiC Series in Computing. Volume 50 (2017), 148-161


Nature showcases swarms of animals and insects performing various complex tasks efficiently where capabilities of individuals alone in the swarm are often quite limited. Swarm intelligence is observed when agents in the swarm follow simple rules which enable the swarm to perform certain complex tasks. This decentralized approach of nature has inspired the artificial intelligence community to apply this approach to engineered systems. Such systems are said to have no single point of failure and thus tend be more resilient. The aim of this paper is to put this notion of resilience to the test and quantify the robustness of two swarm algorithms, namely ¸"swarmtaxis" and "FSTaxis". The first simulation results of the effects of introducing an impairment in agent-to-agent interactions in these two swarm algorithms are presented in this paper. While the FSTaxis algorithm shows a much higher resilience to agent-to-agent communication failure, both the FSTaxis and swarmtaxis algorithms are found to have a non-zero tolerance towards such failures.

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