Self-Organization in Biological Systems
Self-Organization in Biological Systems
Minimalist coherent swarming of wireless networked autonomous mobile robots
ICSAB Proceedings of the seventh international conference on simulation of adaptive behavior on From animals to animats
Aggregating Robots Compute: An Adaptive Heuristic for the Euclidean Steiner Tree Problem
SAB '08 Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats
Cells and Robots: Modeling and Control of Large-Size Agent Populations
Cells and Robots: Modeling and Control of Large-Size Agent Populations
Space-Time Continuous Models of Swarm Robotic Systems: Supporting Global-to-Local Programming
Space-Time Continuous Models of Swarm Robotic Systems: Supporting Global-to-Local Programming
A model of symmetry breaking in collective decision-making
SAB'10 Proceedings of the 11th international conference on Simulation of adaptive behavior: from animals to animats
Multi-level spatial modeling for stochastic distributed robotic systems
International Journal of Robotics Research
Superlinear physical performances in a SWARM-BOT
ECAL'05 Proceedings of the 8th European conference on Advances in Artificial Life
Analysis of emergent symmetry breaking in collective decision making
Neural Computing and Applications - Special Issue on Theory and applications of swarm intelligence
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The search for generally applicable methods in swarm intelligence aims to gain new insights about natural swarms and to develop design methodologies for artificial swarms. The ideal would be a 'swarm calculus' that allows to calculate key features such as expected swarm performance and robustness on the basis of a few parameters. A path towards this ideal is to find methods and models that have maximal generality. We report two models that might be examples of exceptional generality. First, we present an abstract model that describes the performance of a swarm depending on the swarm density based on the dichotomy between cooperation and interference. Second, we give an abstract model for decision making that is inspired by urn models. A parameter, that controls the feedback based on the current consensus, allows to understand the effects of an increasing probability for positive feedback over time in a decision making system.