The dynamics of collective sorting robot-like ants and ant-like robots
Proceedings of the first international conference on simulation of adaptive behavior on From animals to animats
Representations for artificial organisms
Proceedings of the first international conference on simulation of adaptive behavior on From animals to animats
Proceedings of the second international conference on From animals to animats 2 : simulation of adaptive behavior: simulation of adaptive behavior
Collective robotics: from social insects to robots
Adaptive Behavior
Diversity and adaptation in populations of clustering ants
SAB94 Proceedings of the third international conference on Simulation of adaptive behavior : from animals to animats 3: from animals to animats 3
Collective sorting and segregation in robots with minimal sensing
Proceedings of the fifth international conference on simulation of adaptive behavior on From animals to animats 5
Robots, crickets and ants: models of neural control of chemotaxis and phonotaxis
Neural Networks - Special issue on neural control and robotics: biology and technology
Noise and the Reality Gap: The Use of Simulation in Evolutionary Robotics
Proceedings of the Third European Conference on Advances in Artificial Life
A Probabilistic Model for Understanding and Comparing Collective Aggregation Mechansims
ECAL '99 Proceedings of the 5th European Conference on Advances in Artificial Life
Cooperative mobile robotics: antecedents and directions
IROS '95 Proceedings of the International Conference on Intelligent Robots and Systems-Volume 1 - Volume 1
Evolving annular sorting in ant-like agents
ECAL'05 Proceedings of the 8th European conference on Advances in Artificial Life
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This study shows that a task as complicated as patch sorting can be accomplished with a 'minimalist' solution employing four simple rules. The solution is an extension of the object clustering research of Beckers et al. [1] and the object sorting research of Melhuish et al. [2]. Beckers et al. [1] used a very simple mechanism and achieved puck clustering in an arena with simple robots. Melhuish et al. [2] extended this technique to sort two objects, again using simple robots and a simple mechanism. The new mechanism reported in this paper, explores the sorting of any number of different objects into separate clusters. The method works by comparing two objects: the object the robot is carrying and, using a special antenna, the object with which the robot has collided. The results in this paper provide a demonstration of the success of this n-colour mechanism.