Authors:
Danielli A. Lima
1
;
Claudiney R. Tinoco
2
;
Juan M. N. Viedman
2
and
Gina M. B. Oliveira
2
Affiliations:
1
Universidade Federal de Uberlandia UFU, Faculdade de Computacao and Instituto Federal do Triangulo Mineiro IFTM, Brazil
;
2
Universidade Federal de Uberlandia UFU and Faculdade de Computacao, Brazil
Keyword(s):
Cellular Automata, Multi-agents control, Intelligent Swarms, Parallel Synchronization, Foraging Task, Multi-objective Search.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Bioinformatics
;
Biomedical Engineering
;
Collective Intelligence
;
Enterprise Information Systems
;
Hybrid Intelligent Systems
;
Information Systems Analysis and Specification
;
Methodologies and Technologies
;
Mobile Agents
;
Operational Research
;
Simulation
;
Soft Computing
Abstract:
Multiple agent systems can be applied to foraging tasks, thus solving this problem in a cooperative intelligent
approach using cellular automata modeling. The objective is to construct an algorithm that performs foraging
task correctly in Webots EDU simulation platform using robot architecture and also improves the individual
controller model of each intelligent agent, using e-Puck devices properly. The proposed communication model
has taken into account some cellular automata specifications, such as, the need for parallel synchronization,
localization and accuracy of information dependency. After several simulations in Webots EDU, evaluating
different approaches, the proposed communication model presented promising results on the parallel multi-robot
foraging performance being pertinent in intelligent swarm robotics context.