Paper Info
Title
Exploring Knowledge And Population Swarms Via An Agent-Based Cultural Algorithms Simulation Toolkit (Cat)
Abstract
Cultural Algorithms employ a basic set of knowledge sources, each related to knowledge observed in various social species. These knowledge sources are then combined to direct the decisions of the individual agents in solving optimization problems. While many successful real-world applications of Cultural Algorithms have been produced, we are interested in studying the fundamental computational processes involved in the use of Cultural Systems as problem solvers. Here we describe a Java-based toolkit system, the Cultural Algorithm Toolkit (CAT) developed in the Repast Symphony Simulation environment. The system allows users to easily configure and visualize the problem solving process of a Cultural Algorithm. Currently the system supports predator/prey problem solving in a "Cones World" environment as well as a suite of benchmark problems in engineering design. Example runs of a predator prey example are presented to demonstrate the systems' capabilities.
Year
DOI
Venue
2007
10.1109/CEC.2007.4424813
2007 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-10, PROCEEDINGS
Keywords
Field
DocType
learning curve,java,data visualization,optimization problem,multi agent systems,real time
Population,Mathematical optimization,Suite,Computer science,Algorithm,Multi-agent system,Engineering design process,Cultural algorithm,Java,Optimization problem,Cultural system
Conference
Citations 
PageRank 
References 
5
0.52
6
Authors
2
Name
Order
Citations
PageRank
Robert G. Reynolds1610188.20
Mostafa Z. Ali225219.32