Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Improved Steiner tree approximation in graphs
SODA '00 Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms
Autonomous Robots
Approximation Hardness of the Steiner Tree Problem on Graphs
SWAT '02 Proceedings of the 8th Scandinavian Workshop on Algorithm Theory
Some NP-complete geometric problems
STOC '76 Proceedings of the eighth annual ACM symposium on Theory of computing
Guest Column: NP-complete problems and physical reality
ACM SIGACT News
The I-SWARM project: intelligent small world autonomous robots for micro-manipulation
SAB'04 Proceedings of the 2004 international conference on Swarm Robotics
Towards swarm calculus: universal properties of swarm performance and collective decisions
ANTS'12 Proceedings of the 8th international conference on Swarm Intelligence
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It is becoming state-of-the-art to form large-scale multi-agent systems or artificial swarms showing adaptive behavior by constructing high numbers of cooperating, embodied, mobile agents (robots). For the sake of space- and cost-efficiency such robots are typically miniaturized and equipped with only few sensors and actuators resulting in rather simple devices. In order to overcome these constraints, bio-inspired concepts of self-organization and emergent properties are applied. Thus, accuracy is usually not a trait of such systems, but robustness and fault tolerance are. It turns out that they are applicable to even hard problems and reliably deliver approximated solutions. Based on these principles we present a heuristic for the Euclidean Steiner tree problem which is NP-hard. Basically, it is the problem of connecting objects in a plane efficiently. The proposed system is investigated from two different viewpoints: computationally and behaviorally. While the performance is, as expected, clearly suboptimal but still reasonably well, the system is adaptive and robust.