Scientific journal paper Q1
Evolving flocking in embodied agents based on local and global application of Reynolds’ rules
Rita Parada Ramos (Ramos, R. P:); Sancho Moura Oliveira (Oliveira, S. M.); Susana Margarida Vieira (Vieira, S. M.); Anders Christensen (Christensen, A. L.);
Journal Title
PLoS One
Year (definitive publication)
2019
Language
English
Country
United States of America
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Times Cited: 14

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Abstract
In large scale systems of embodied agents, such as robot swarms, the ability to flock is essential in many tasks. However, the conditions necessary to artificially evolve self-organised flocking behaviours remain unknown. In this paper, we study and demonstrate how evolutionary techniques can be used to synthesise flocking behaviours, in particular, how fitness functions should be designed to evolve high-performing controllers. We start by considering Reynolds' seminal work on flocking, the boids model, and design three components of a fitness function that are directly based on his three local rules to enforce local separation, cohesion and alignment. Results show that embedding Reynolds' rules in the fitness function can lead to the successful evolution of flocking behaviours. However, only local, fragmented flocking behaviours tend to evolve when fitness scores are based on the individuals' conformity to Reynolds' rules. We therefore modify the components of the fitness function so that they consider the entire group of agents simultaneously, and find that the resulting behaviours lead to global flocking. Furthermore, the results show that alignment need not be explicitly rewarded to successfully evolve flocking. Our study thus represents a significant step towards the use of evolutionary techniques to synthesise collective behaviours for tasks in which embodied agents need to move as a single, cohesive group.
Acknowledgements
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Keywords
  • Computer and Information Sciences - Natural Sciences
  • Other Engineering and Technology Sciences - Engineering and Technology
Funding Records
Funding Reference Funding Entity
UID/EEA/50008/2019 Fundação para a Ciência e a Tecnologia