Flocks, herds and schools: A distributed behavioral model
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Distributed Anonymous Mobile Robots: Formation of Geometric Patterns
SIAM Journal on Computing
An Behavior-based Robotics
Artificial Life: A Report from the Frontier Where Computers Meet Biology
Artificial Life: A Report from the Frontier Where Computers Meet Biology
Modeling and simulation for exploring human-robot team interaction requirements
Proceedings of the 33nd conference on Winter simulation
Neural network guided robot collectivity: an experimental setup
NN'06 Proceedings of the 7th WSEAS International Conference on Neural Networks
From balls and bins to points and vertices
ISAAC'05 Proceedings of the 16th international conference on Algorithms and Computation
Effects of Multi-Robot Team Formations on Distributed Area Coverage
International Journal of Swarm Intelligence Research
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Micro-robots will soon be available for deployment by the thousands. Consequently, controlling and coordinating a force this large to accomplish a prescribed task is of great interest. This paper describes a flexible architecture for modeling thousands of autonomous agents simultaneously. The agents' behavior is based on a subsumption architecture in which individual behaviors are prioritized with respect to all others. The primary behavior explored in this work is a group formation behavior based on social potential fields (Reif and Wang 1999). This paper extends the social potential field model by introducing a neutral zone within which other behaviors may exhibit themselves. Previous work with social potential fields has been restricted to models of "perfect" autonomous agents. The paper evaluates the effect of social potential fields in the presence of agent death (failure) and imperfect sensory input.