Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
The E-CELL project: towards integrative simulation of cellular processes
RECOMB '00 Proceedings of the fourth annual international conference on Computational molecular biology
Illustrating evolutionary computation with Mathematica
Illustrating evolutionary computation with Mathematica
Computational Modeling of Genetic and Biochemical Networks (Computational Molecular Biology)
Computational Modeling of Genetic and Biochemical Networks (Computational Molecular Biology)
SwarmArt: interactive art from swarm intelligence
Proceedings of the 12th annual ACM international conference on Multimedia
Fractal Evolver: Interactive Evolutionary Design of Fractals with Grid Computing
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
Research frontier: the evolution of swarm grammars-growing trees, crafting art, and bottom-up design
IEEE Computational Intelligence Magazine
A graph-based developmental swarm representation and algorithm
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
Adaptive modularization of the MAPK signaling pathway using the multiagent paradigm
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part II
The swarming body: simulating the decentralized defenses of immunity
ICARIS'06 Proceedings of the 5th international conference on Artificial Immune Systems
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We present our latest version of a swarm-based, 3-dimensional model of the lactose (lac) operon gene regulatory system. The lac operon is a well-understood genetic switch capable of self-regulation dependent on the energy source of lactose. Our model includes a 3D visualisation which simulates proteins as agents with physical properties that interact with DNA, molecules, and other proteins, incorporating many of the important aspects of a genetic regulatory system. Our model utilizes a decentralized swarm approach with multiple agents acting independently -- according to local interaction rules -- to exhibit complex emergent behaviours, which constitute the externally observable and measurable switching behaviour.