Genetic algorithms for optimization of boids model

Authors:
Yen-Wei Chen;Kanami Kobayashi;Xinyin Huang;Zensho Nakao
Affiliations:
School of Information Science and Eng., Ristumeikan Univ., Shiga, Japan;School of Information Science and Eng., Ristumeikan Univ., Shiga, Japan;School of Education, Soochow University, Suzhou, Jiangsu, China;Faculy of Eng., Univ. of the Ryukyus, Okinawa, Japan
Venue:
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
Year:
2006

Citing 3
Cited 1

Flocks, herds and schools: A distributed behavioral model

SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning
OpenGL(R) 1.4 Reference Manual (4th Edition)

OpenGL(R) 1.4 Reference Manual (4th Edition)

Application of Interactive Genetic Algorithms to Boid Model Based Artificial Fish Schools

KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we present an extended boids model for simulating the aggregate moving of fish schools in a complex environment. Three behavior rules are added to the extended boids model: following a feed; avoiding obstacle; avoiding enemy boids. The moving vector is a linear combination of every behavior rule vector, and the coefficients should be optimized. We also proposed a genetic algorithm to optimize the coefficients. Experimental results show that by using the GA-based optimization, the aggregate motions of fish schools become more realistic and similar to behaviors of real fish world.