Multi-Cellular Techniques

2007 ◽  
pp. 16-27
Author(s):  
C. Anderson
Keyword(s):  
Problem Solving ◽  
Task Allocation ◽  
Lessons Learned ◽  
Collective Phenomena ◽  
Distributed Problem Solving ◽  
Insect Societies ◽  
Nature Inspired Computing ◽  
History Of ◽  
Multi Agent ◽  
Problem Solving Task

Social insects—ants, bees, wasps, and termites—and the distributed problem-solving, multi-agent paradigm that they represent, have been enormously influential in nature-inspired computing. Insect societies have been a source of inspiration and amazement for centuries, but only in the last 25 years or so have we made significant inroads to both understanding just how various collective phenomena arise and are governed, and how we can use the lessons and insights garnered from sociobiological research for more practical purposes. In this chapter, we provide a very brief history of the field, detailing some of the key phenomena, mechanisms, and lessons learned, and a quick tour of some of the different types of applications to which this knowledge has been put to use, including but certainly not limited to distributed problem solving, task allocation, search, and collective robotics.

Multi-agent collaborative service and distributed problem solving

2004 ◽  
Vol 5 (3) ◽  
pp. 191-206 ◽  
Author(s):  
Jiming Liu ◽  
Xiaolong Jin ◽  
Yi Tang
Keyword(s):  
Problem Solving ◽  
Distributed Problem Solving ◽  
Multi Agent

Design and Implementation of Swam Robotics using Flood Fill Algorithm

2017 ◽  
Vol 6 (4) ◽  
pp. 269
Author(s):  
Mary swarna Latha gade ◽  
GAjitha GAjitha ◽  
Deepthi. S
Keyword(s):  
Problem Solving ◽  
Wireless Communication ◽  
Global Model ◽  
Centralized Control ◽  
Moderate Size ◽  
Design And Implementation ◽  
Distributed Problem Solving ◽  
Multi Agent ◽  
Flood Fill

<p>Swam Intelligence provides a basis with which it is possible to explore collective (or distributed) problem solving without centralized control or the provision of a global model. This paper presents design and implementation of swam robotics in a multi-agent environment. At the beginning, robot agents are ignorant of the maze. The robots are programmed with Flood fill algorithm to solve maze. The robot scans maze and stores the values in EEPROM. The robot agent shares the information to other robot agents through wireless communication. The proposed flood fill algorithm is found to be effective tool for solving maze of moderate size.</p>

scholarly journals BRIEF HISTORY OF NATURAL SCIENCES FOR NATURE-INSPIRED COMPUTING IN ENGINEERING

2016 ◽  
Vol 22 (3) ◽  
pp. 287-301 ◽  
Author(s):  
Nazmul SIDDIQUE ◽  
Hojjat ADELI
Keyword(s):  
Problem Solving ◽  
Natural Sciences ◽  
The Past ◽  
Body Of Knowledge ◽  
Nature Inspired Computing ◽  
History Of

The goal of the authors is adroit integration of three mainstream disciplines of the natural sciences, physics, chemistry and biology to create novel problem solving paradigms. This paper presents a brief history of the develop­ment of the natural sciences and highlights some milestones which subsequently influenced many branches of science, engineering and computing as a prelude to nature-inspired computing which has captured the imagination of computing researchers in the past three decades. The idea is to summarize the massive body of knowledge in a single paper suc­cinctly. The paper is organised into three main sections: developments in physics, developments in chemistry, and de­velopments in biology. Examples of recently-proposed computing approaches inspired by the three branches of natural sciences are provided.

scholarly journals Pouw, Wassenburg, Hostetter, de Koning, & Paas. Does Gesture Strengthen Sensorimotor Knowledge of Objects? The Case of the Size-Weight Illusion

2018 ◽  
Author(s):  
Wim T. J. L. Pouw ◽  
Stephanie I. Wassenburg ◽  
Autumn Hostetter ◽  
Bjorn de Koning ◽  
Fred Paas
Keyword(s):  
Problem Solving ◽  
Control Task ◽  
History Of ◽  
Sensorimotor Interactions ◽  
Weight Illusion ◽  
Sensorimotor Knowledge ◽  
Problem Solving Task

Co-speech gestures have been proposed to strengthen sensorimotor knowledge related to objects’ weight and manipulability. In this pre-registered study (N =159) designed to provide a robust, direct, and detailed test of this proposal, participants practiced a problem-solving task with small and large objects that were designed to induce a size-weight illusion (i.e., objects weigh the same but are experienced as different in weight). Participants then explained the task with or without co-speech gesture, or completed a control task. Afterwards, participants judged the heaviness of objects from memory and then while holding them. Confirmatory analyses revealed that gesturing did not affect heaviness ratings. However, exploratory analyses revealed reliable correlations between participants’ heaviness judgments from memory and a) the amount of gestures produced that simulated actions, and b) the kinematics of the lifting phases of those gestures. These findings suggest that gestures emerge as sensorimotor imaginings that are governed by the agent’s history of sensorimotor interactions with the environment.

Scientific Problem Solving in a Virtual Laboratory: A Comparison Between Individuals and Pairs

2008 ◽  
Vol 67 (2) ◽  
pp. 71-83 ◽  
Author(s):  
Yolanda A. Métrailler ◽  
Ester Reijnen ◽  
Cornelia Kneser ◽  
Klaus Opwis
Keyword(s):  
Visual Search ◽  
Problem Solving ◽  
Process Data ◽  
Scientific Problem ◽  
Domain Specific ◽  
Scientific Problem Solving ◽  
Before And After ◽  
Verbal Data ◽  
Psychological Knowledge ◽  
Problem Solving Task

This study compared individuals with pairs in a scientific problem-solving task. Participants interacted with a virtual psychological laboratory called Virtue to reason about a visual search theory. To this end, they created hypotheses, designed experiments, and analyzed and interpreted the results of their experiments in order to discover which of five possible factors affected the visual search process. Before and after their interaction with Virtue, participants took a test measuring theoretical and methodological knowledge. In addition, process data reflecting participants’ experimental activities and verbal data were collected. The results showed a significant but equal increase in knowledge for both groups. We found differences between individuals and pairs in the evaluation of hypotheses in the process data, and in descriptive and explanatory statements in the verbal data. Interacting with Virtue helped all students improve their domain-specific and domain-general psychological knowledge.

Moving to Solution

2013 ◽  
Vol 60 (6) ◽  
pp. 403-409 ◽  
Author(s):  
K. Werner ◽  
M. Raab
Keyword(s):  
Problem Solving ◽  
Embodied Cognition ◽  
Cognitive Functions ◽  
Problem Space ◽  
Arm Swing ◽  
String Problem ◽  
Problem Solving Process ◽  
Problem Solving Task ◽  
Bodily Movements

Embodied cognition theories suggest a link between bodily movements and cognitive functions. Given such a link, it is assumed that movement influences the two main stages of problem solving: creating a problem space and creating solutions. This study explores how specific the link between bodily movements and the problem-solving process is. Seventy-two participants were tested with variations of the two-string problem (Experiment 1) and the water-jar problem (Experiment 2), allowing for two possible solutions. In Experiment 1 participants were primed with arm-swing movements (swing group) and step movements on a chair (step group). In Experiment 2 participants sat in front of three jars with glass marbles and had to sort these marbles from the outer jars to the middle one (plus group) or vice versa (minus group). Results showed more swing-like solutions in the swing group and more step-like solutions in the step group, and more addition solutions in the plus group and more subtraction solutions in the minus group. This specificity of the connection between movement and problem-solving task will allow further experiments to investigate how bodily movements influence the stages of problem solving.

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