stigmergy

Structural Stigmergy Model

Structural Stigmergy Model nonstandardstudio #stigmergy #structuralStigmergy #shellStructures #catenary

Articulation of structural morphologies – through principles of stigmergic collaboration and structural coupling.

By self-regulating critical variables of force distribution within a structural system, the ecology of agents is developing an automatic mechanism of self-regulation – homeostasis/autopoiesis system – where the system becomes self-producing, allowing for a correlated and differentiated multi-system. Where like in natural systems, compositions are so highly integrated that they cannot be easily decomposed into independent subsystems. It becomes a system with self-reference and self-regulation which further evolves by using structural coupling. Therefore recognizing that the outside influences cannot shape the system’s internal structure, but act only as a trigger that causes the structure to alter its current attractors.

There were 2xNVidia GTX780Ti used in this study, having in total a combined 5760CUDA cores (2880 each), running on a machine 2 x Intel Core i7-4930k @ 3.40GHz and Corsair DOMINATOR Platinum Series 64GB DDR4 DRAM 2800MHz.

References:

[1]Emergence: The Connected Lives of Ants, Brains, Cities, and Software by Steven Johnson

[2]The Myth of the Framework: In Defense of Science and Rationality by Karl Popper

[3] Bonabeau E., M. Dorigo, G. Théraulaz. Swarm Intelligence: From Natural to Artificial System s. Santa Fe Institute in the Sciences of the Complexity, Oxford University Press, New York, Oxford, 1999.
[4] Chialvo, Dante R., Millonas, Mark M. “How Swarms Build Cognitive Maps” . In Luc Steels (Ed.), The Biology and Technology of Intelligent Autonomous Agents , (144) pp. 439-450, NATO ASI Series, 1995.
[5] Vitorino Ramos, Filipe Almeida, Artificial Ant Colonies in Digital Image Habi­tats – A Mass Behaviour Effect Study on Pattern Recognition, Proceedings of ANTS’2000 – 2nd International Workshop on Ant Algorithms (From Ant Colonies to Artificial Ants), Marco Dorigo, Martin Middendorf & Thomas Stüzle (Eds.), pp. 113 – 116, Brussels, Belgium, 7 – 9 Sep. 2000.

US equivalent
GPU: 2xNVidia GTX780Ti
CPU: 2 x Intel Core i7-4930k @ 3.40GH
RAM: Corsair DOMINATOR Platinum Series 64GB DDR4 DRAM 2800MHz

References:

[1]Emergence: The Connected Lives of Ants, Brains, Cities, and Software by Steven Johnson

[2]The Myth of the Framework: In Defense of Science and Rationality by Karl Popper

[3] Bonabeau E., M. Dorigo, G. Théraulaz. Swarm Intelligence: From Natural to Artificial System s. Santa Fe Institute in the Sciences of the Complexity, Oxford University Press, New York, Oxford, 1999.
[4] Chialvo, Dante R., Millonas, Mark M. “How Swarms Build Cognitive Maps” . In Luc Steels (Ed.), The Biology and Technology of Intelligent Autonomous Agents , (144) pp. 439-450, NATO ASI Series, 1995.
[5] Vitorino Ramos, Filipe Almeida, Artificial Ant Colonies in Digital Image Habi­tats – A Mass Behaviour Effect Study on Pattern Recognition, Proceedings of ANTS’2000 – 2nd International Workshop on Ant Algorithms (From Ant Colonies to Artificial Ants), Marco Dorigo, Martin Middendorf & Thomas Stüzle (Eds.), pp. 113 – 116, Brussels, Belgium, 7 – 9 Sep. 2000.