Flocks, herds and schools: A distributed behavioral model
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Collective robotics: from social insects to robots
Adaptive Behavior
Sequential behavior and learning in evolved dynamical neural networks
Adaptive Behavior
Evolving mobile robots in simulated and real environments
Artificial Life
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Stigmergy, self-organization, and sorting in collective robotics
Artificial Life
Evolutionary Robotics: The Biology,Intelligence,and Technology
Evolutionary Robotics: The Biology,Intelligence,and Technology
Evolving collective behavior in an artificial ecology
Artificial Life
Cooperative Mobile Robotics: Antecedents and Directions
Autonomous Robots
Heterogeneous Teams of Modular Robots for Mapping and Exploration
Autonomous Robots
Self-Organization in Biological Systems
Self-Organization in Biological Systems
Mobile Robot Miniaturisation: A Tool for Investigation in Control Algorithms
The 3rd International Symposium on Experimental Robotics III
Distributed Robotic Manipulation: Experiments in Minimalism
The 4th International Symposium on Experimental Robotics IV
Evolving mobile robots able to display collective behaviors
Artificial Life
Autonomous Robots
Swarm-Bot: A New Distributed Robotic Concept
Autonomous Robots
Evolving Self-Organizing Behaviors for a Swarm-Bot
Autonomous Robots
Emergence of Collective Behavior in Evolving Populations of Flying Agents
Genetic Programming and Evolvable Machines
Cooperative Multi-Agent Learning: The State of the Art
Autonomous Agents and Multi-Agent Systems
Analysis of Dynamic Task Allocation in Multi-Robot Systems
International Journal of Robotics Research
Modeling Phase Transition in Self-organized Mobile Robot Flocks
ANTS '08 Proceedings of the 6th international conference on Ant Colony Optimization and Swarm Intelligence
Strengths and synergies of evolved and designed controllers: A study within collective robotics
Artificial Intelligence
Genetic team composition and level of selection in the evolution of cooperation
IEEE Transactions on Evolutionary Computation
Evolution of collective behavior in a team of physically linked robots
EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing
From solitary to collective behaviours: decision making and cooperation
ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
Self-Organized Coordinated Motion in Groups of Physically Connected Robots
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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Organisms that live in groups, from microbial symbionts to social insects and schooling fish, exhibit a number of highly efficient cooperative behaviors, often based on role taking and specialization. These behaviors 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 for decentralized collective robotic tasks based on principles of self-organization. The article first presents a taxonomy of role-taking and specialization mechanisms related to evolved neural network controllers. Then it introduces two cooperation tasks, which can be accomplished by either role taking or specialization, and uses these tasks to compare four different genetic algorithms to evaluate their capacity to evolve a suitable behavioral strategy, which depends on the task demands. Interestingly, only one of the four algorithms, which appears to have more biological plausibility, is capable of evolving role taking or specialization when they are needed. The results are relevant for both collective robotics and biology, as they can provide useful hints on the different processes that can lead to the emergence of specialization in robots and organisms.