Evolving dynamical neural networks for adaptive behavior
Adaptive Behavior
Evolutionary robotics and the radical envelope-of-noise hypothesis
Adaptive Behavior
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Computational principles of mobile robotics
Computational principles of mobile robotics
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Evolutionary Robotics: The Biology,Intelligence,and Technology
Evolutionary Robotics: The Biology,Intelligence,and Technology
Swarm-Bot: A New Distributed Robotic Concept
Autonomous Robots
Self-organisation and communication in groups of simulated and physical robots
Biological Cybernetics
Robots, insects and swarm intelligence
Artificial Intelligence Review
Connection Science
Evolution of acoustic communication between two cooperating robots
ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
From solitary to collective behaviours: decision making and cooperation
ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
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Communication is a point of central importance in swarms of robots. This paper describes a set of simulations in which artificial evolution is used as a means to engineer robot neuro-controllers capable of guiding groups of robots in a categorisation task by producing appropriate actions. Communicative behaviour emerges, notwithstanding the absence of explicit selective pressure (coded into the fitness function) to favour signalling over non-signalling groups. Post-evaluation analyses illustrate the adaptive function of the evolved signals and show that they are tightly linked to the behavioural repertoire of the agents. Finally, our approach for developing controllers is validated by successfully porting one evolved controller on real robots.