Collective Intelligence

2011 ◽  
pp. 280-287 ◽  
Author(s):  
Paulo Garrido ◽  
Wilfried Lemahieu
Keyword(s):  
Collective Intelligence ◽  
Previous Knowledge ◽  
Intelligent Behavior ◽  
Absolute Concept

Intelligence is taken here as the ability for attaining goals or for solving problems that put at work responsiveness of the solver to the situation where the goal or problem arises and use of its previous knowledge and experience. Let one notice that this definition means that intelligence or intelligent behavior is not an absolute concept in at least three ways: • Intelligence is relative to the goal or problem being solved. • Intelligence is relative to the situation where the goal arises. • Intelligence is relative to the knowledge and experience of the solver. Usually, intelligence is conceived as a property of individuals. In recent years, the recognizance has grown that this conception is too narrow. It makes sense and it is most useful to consider the intelligence of groups of individuals, whether small or very large. Such intelligence is still the intelligence of one entity— the group—but it is made of the ways individual intelligences are orchestrated or coordinate themselves. This being given, collective intelligence (CI) is defined here simply as the intelligence of entities constituted by several or many individuals. As taken, CI is about the intelligent behavior of entities which are conceived from the beginning as not being atomic.

scholarly journals A review of swarm intelligence algorithms deployment for scheduling and optimization in cloud computing environments

2021 ◽  
Vol 7 ◽  
pp. e696
Author(s):  
Yousef Qawqzeh ◽  
Mafawez T. Alharbi ◽  
Ayman Jaradat ◽  
Khalid Nazim Abdul Sattar
Keyword(s):  
Cloud Computing ◽  
Swarm Intelligence ◽  
Optimization Problems ◽  
Collective Intelligence ◽  
Pso Algorithm ◽  
Cloud Computing Environment ◽  
Bee Colony ◽  
Self Organized ◽  
Intelligent Behavior ◽  
New Si

Background This review focuses on reviewing the recent publications of swarm intelligence algorithms (particle swarm optimization (PSO), ant colony optimization (ACO), artificial bee colony (ABC), and the firefly algorithm (FA)) in scheduling and optimization problems. Swarm intelligence (SI) can be described as the intelligent behavior of natural living animals, fishes, and insects. In fact, it is based on agent groups or populations in which they have a reliable connection among them and with their environment. Inside such a group or population, each agent (member) performs according to certain rules that make it capable of maximizing the overall utility of that certain group or population. It can be described as a collective intelligence among self-organized members in certain group or population. In fact, biology inspired many researchers to mimic the behavior of certain natural swarms (birds, animals, or insects) to solve some computational problems effectively. Methodology SI techniques were utilized in cloud computing environment seeking optimum scheduling strategies. Hence, the most recent publications (2015–2021) that belongs to SI algorithms are reviewed and summarized. Results It is clear that the number of algorithms for cloud computing optimization is increasing rapidly. The number of PSO, ACO, ABC, and FA related journal papers has been visibility increased. However, it is noticeably that many recently emerging algorithms were emerged based on the amendment on the original SI algorithms especially the PSO algorithm. Conclusions The major intention of this work is to motivate interested researchers to develop and innovate new SI-based solutions that can handle complex and multi-objective computational problems.

Unfold Collective Intelligence!

2012 ◽  
Vol 107 (3) ◽  
pp. 152-157 ◽  
Author(s):  
Pascal Krenz ◽  
Jens P. Wulfsberg ◽  
Franz-L. Bruhns
Keyword(s):  
Collective Intelligence

Rancang Bangun Sistem Rekomendasi Resep Masakan Khas Indonesia Menggunakan Metode Collaboration Collective Intelligence dan Slope One

2018 ◽  
Vol 9 (2) ◽  
pp. 88-96 ◽  
Author(s):  
Adhi Kusnadi ◽  
Daniel Daniel
Keyword(s):  
Collective Intelligence ◽  
The Public ◽  
Index Terms ◽  
Previous User

Today, recipes are not just physical, but some are digital. So users do not have to store recipe books that have been purchased to find recipes for a dish. One of a website providing recommendations for digital recipe guides is dapursaji. This application helps users to search for recipes only by entering the ingredients of the food owned by the user. And will produce a list of dishes that use the material entered by the previous user. In addition there will be related recommendations after opening one of the recipes after the search. Not only that, this website can also provide the freedom to innovate, by means of all users can fill a new recipe in accordance with the innovation and creation itself. Then the recipe will be published and read by the public. Collaborative Collective Intelligence and Slope One methods are implemented in this design, and evaluation results show that as many as 89% of users surveyed have been satisfied with the suitability and usefulness of the built system. Index Terms—recipes, dish, collaborative Collective Intelligence, slope one

Subjective factors affecting gun shooting accuracy among employees of internal affairs agencies in process of learning

2020 ◽  
Vol 2020 (4) ◽  
pp. 198-206
Author(s):  
Anton Rozhkov ◽  
Anton Popov ◽  
Vitaliy Balahonskiy
Keyword(s):  
Subjective Experience ◽  
Statistical Significance ◽  
Self Regulation ◽  
Sensorimotor Coordination ◽  
Factors Affecting ◽  
Intelligent Behavior ◽  
Experience Of Stress ◽  
Firing Line ◽  
High Level ◽  
In Fire

The article is devoted to the study of subjective factors affecting shooting accuracy of law enforcement officers. The empirical study identified some subjective factors reducing gun shooting accuracy and effectiveness among law enforcers. These characteristics include sensorimotor coordination and subjective experience of stress during the shooting process. Scientific analysis made it possible to determine statistical significance of the influence of these factors on the accuracy of shooting. To increase the effectiveness of shooting among officers with a low index of sensorimotor coordination, the authors suggest using exercises aimed at cultivating sensorimotor coordination in fire training classes. While working with employees being under a high level of subjectively experienced stress, more attention should be paid to training techniques to overcome stress and form intelligent behavior in extreme situations. The authors also draw readers’ attention to factors increasing the effectiveness of shooting: officers’ ability to determine the subjective level of stress, their knowledge of emotional self-regulation techniques, knowledge of the sequence of their actions in the firing line.

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