Integrated systems based on behaviors
ACM SIGART Bulletin
Survivable robotic systems: reactive and homeostatic control
Robotics and remote systems for hazardous environments
Creativity in evolution: individuals, interactions, and environments
Creative evolutionary systems
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
The Legion System: A Novel Approach to Evolving Hetrogeneity for Collective Problem Solving
Proceedings of the European Conference on Genetic Programming
The Advantages of Evolutionary Computation
Biocomputing and emergent computation: Proceedings of BCEC97
Fitness functions in evolutionary robotics: A survey and analysis
Robotics and Autonomous Systems
Evolving teamwork and coordination with genetic programming
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
The dynamics of action selection
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
Multi-agent learning of heterogeneous robots by evolutionary subsumption
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Fractal gene regulatory networks for robust locomotion control of modular robots
SAB'10 Proceedings of the 11th international conference on Simulation of adaptive behavior: from animals to animats
The balance between initial training and lifelong adaptation in evolving robot controllers
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Ultrastable neuroendocrine robot controller
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Multi-robot, dynamic task allocation: a case study
Intelligent Service Robotics
Vector-valued function estimation by grammatical evolution for autonomous robot control
Information Sciences: an International Journal
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This article describes a robotic system which uses evolution to continuously adapt a group of heterogeneous robots to their current environment while assigning tasks to these robots using an endocrine-based system. The tasks are allocated dependent on the robots芒聙聶 current ability to perform the task and whether the task is being done by another robot. A series of experiments is presented taking the work from an evolutionary training phase, through simulation trials, to experiments on real robots. The real robot trials show task swapping dependent on the robots芒聙聶 ability to perform each task.