User:T57fd/Swarm intelligence

This is the sandbox to work on improving Swarm Intelligence

Crowd simulation[edit]
[PLAN: First paragraph should be a summation of crowd simulation applications: ie building design/evacuation planning, film, computer games, medicine, plane passenger boarding] Then the detail paragraphs with instances can be developed.]

Crowd simulation using a Multi-Species Artificial Bee Colony algorithm can be used to improve human crowd evacuation efficiency Artists are using swarm technology as a means of creating complex interactive systems or simulating crowds.[citation needed]

Instances[edit]
The Lord of the Rings film trilogy made use of similar technology, known as Massive (software), during battle scenes. Swarm technology is particularly attractive because it is cheap, robust, and simple.

Stanley and Stella in: Breaking the Ice was the first movie to make use of swarm technology for rendering, realistically depicting the movements of groups of fish and birds using the Boids system.[citation needed]

Tim Burton's Batman Returns also made use of swarm technology for showing the movements of a group of bats.

Airlines have used swarm theory to simulate passengers boarding a plane. Southwest Airlines researcher Douglas A. Lawson used an ant-based computer simulation employing only six interaction rules to evaluate boarding times using various boarding methods.(Miller, 2010, xii-xviii).

Human swarming[edit]
Networks of distributed users can be organized into "human swarms" through the implementation of real-time closed-loop control systems. Developed by Louis Rosenberg in 2015, human swarming, also called artificial swarm intelligence, allows the collective intelligence of interconnected groups of people online to be harnessed. The collective intelligence of the group often exceeds the abilities of any one member of the group.

Stanford University School of Medicine published in 2018 a study showing that groups of human doctors, when connected together by real-time swarming algorithms, could diagnose medical conditions with substantially higher accuracy than individual doctors or groups of doctors working together using traditional crowd-sourcing methods. In one such study, swarms of human radiologists connected together were tasked with diagnosing chest x-rays and demonstrated a 33% reduction in diagnostic errors as compared to the traditional human methods, and a 22% improvement over traditional machine-learning.

The University of California San Francisco (UCSF) School of Medicine released a preprint in 2021 about the diagnosis of MRI images by small groups of collaborating doctors. The study showed a 23% increase in diagnostic accuracy when using Artificial Swarm Intelligence (ASI) technology compared to majority voting.

Applications
Swarm Intelligence-based techniques can be used in a number of applications. Existent SI capabilities are being reviewed by the US Air Force for application in offense, defense and threat detection. The European Space Agency is thinking about an orbital swarm for self-assembly and interferometry. NASA is investigating the use of swarm technology for planetary mapping. A 1992 paper by M. Anthony Lewis and George A. Bekey discusses the possibility of using swarm intelligence to control nanobots within the body for the purpose of killing cancer tumors. Conversely al-Rifaie and Aber have used stochastic diffusion search to help locate tumours. Swarm intelligence has also been applied for data mining and cluster analysis. Ant-based models are further subject of modern management theory.


 * Reference to look at for later: Kennedy, J. Handbook of nature-inspired and innovative computing. In Swarm intelligence; Springer: Berlin/Heidelberg, Germany, 2006; pp. 187–219

Applications
Swarm Intelligence-based techniques can be used in a number of applications. The U.S. military is investigating swarm techniques for controlling unmanned vehicles. The European Space Agency is thinking about an orbital swarm for self-assembly and interferometry. NASA is investigating the use of swarm technology for planetary mapping. A 1992 paper by M. Anthony Lewis and George A. Bekey discusses the possibility of using swarm intelligence to control nanobots within the body for the purpose of killing cancer tumors. Conversely al-Rifaie and Aber have used stochastic diffusion search to help locate tumours. Swarm intelligence has also been applied for data mining and cluster analysis. Ant-based models are further subject of modern management theory.