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Biology
Insect Science

Ant-like task allocation and recruitment in cooperative robots

Profile image of Laurent KellerLaurent Keller

2000, Nature

https://doi.org/10.1038/35023164
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4 pages

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Abstract
sparkles

AI

Ant-like task allocation and recruitment behavior among cooperative robots can effectively mimic biological phenomena observed in ant colonies. This study explores how various group sizes and food distributions impact the energy efficiency of robot colonies. Through extensive experimentation and sophisticated statistical analyses, findings suggest enhanced colony performance when employing recruitment strategies in response to clustered food sources, highlighting valuable implications for the design and functioning of cooperative robotic systems.

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    Gianluca Baldassarre

    Artificial Life, 2013

    Organisms that live in groups, from microbial symbionts to social insects and schooling fish, exhibit a number of highly efficient cooperative behaviours, often based on role taking and specialisation. These behaviours are relevant not only for the biologist but also for the engineer interested in decentralized collective robotics. We address these phenomena by carrying out experiments with groups of two simulated robots controlled by neural networks whose connection weights are evolved by using genetic algorithms. These algorithms and controllers are well suited to autonomously find solutions to decentralized collective robotic tasks based on principles of self-organization. The paper first presents a taxonomy of role taking and specialisation mechanisms related to evolved neuralnetwork controllers. Then it introduces two cooperation tasks which can be accomplished by either role taking or specialisation and uses these tasks to compare four different genetic algorithms to evaluate their capacity to evolve a suitable behavioural strategy which depends on the task demands.

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