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Blog: Swarm Research Final Thoughts

Computational Art — Research and Theory


On completing our research project on swarms and swarm art computing and by producing three artefacts as a group (one artefact each), I feel quite benefited for discovering and looking deeper in that era, given that the specific subject was totally unknown to me before. Interviewing Dr. Tim Blackwell, Dr. Mohammad Majid al-Rifaie and Lior Ben Gai (as part of my interview artefact), all experts in a relating field around swarms, helped me put together all the bits and pieces that I was acquiring, by that time, through our exploration or even added new ones. Moreover, the whole process made me think in a broader sphere and through multiple directions, as well as associate terms and characteristics of swarms with wider concepts.

More specifically, as emerged from Dr. al-Rifaie’s interview, the fact that computational or natural swarms, which are capable of performing numerous tasks in both art and science and which are expected to play an even more significant role in the future, are entities that don’t have leaders. The idea of the fact that don’t rely on a leader is quite telling and is something that nature has been doing for millions of years. Everything happens through the local interaction and the exchange of the information. It also means that if at any point you lose the leader within the population, the system is not going to collapse. This utopic concept, rather than being a paradox, could be transferred and form a great paradigm in the human society, which for example, in times of surveillance and political corruption and disbelief is seeking for solutions and getaways, thus towards a more collective behaviour.

Another worth mentioning point from the interview artefact, highlighted possibilities that define the presence and the future of swarm art computing, as well as swarm computing in general. Moreover, Dr. Mohammad al-Rifaie produced a hybrid algorithm by combining the SDS with the PSO algorithms. The first, Stochastic Diffusion Search, is imitating the foraging behaviour of ants and the later, Particle Swarm Optimization, the flocking behaviour of birds.

“The resulting hybrid algorithm is used to sketch novel drawings of an input image, exploiting an artistic tension between the local behaviour of the ‘birds flocking’ — as they seek to follow the input sketch — and the global behaviour of the “ants foraging” — as they seek to encourage the flock to explore novel regions of the canvas.” (Michael Ryan, “The Digital Mind: An exploration of artificial intelligence” 2014).

Additionally, the use of a swarm intelligence algorithm (Stochastic Diffusion Search) in quantifying the level of calcification in the access vessels for EVAR and TEVAR.

Source: Artificial Intelligence on Medium

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