DocumentCode :
2515439
Title :
An improved maze solving algorithm based on an amoeboid organism
Author :
Zhang, Ya Juan ; Zhang, Zi Li ; Deng, Yong
Author_Institution :
Sch. of Comput. & Inf. Sci., Southwest Univ., Chongqing, China
fYear :
2011
fDate :
23-25 May 2011
Firstpage :
1440
Lastpage :
1443
Abstract :
Maze solving algorithm is used to find the shortest path between the source and target point in a given labyrinth. In this paper, an improved algorithm based on existing mathematical model inspired by an amoeboid organism, Physarum polycephalum, is proposed to solve maze solving problems. The positive feedback mechanism in the mathematical model is adopted in our algorithm. Meanwhile, some fuzzy rules generated from experiments are integrated to reduce convergence time and improve the performance of our algorithm. An illustrative example is given to prove the efficiency of the proposed algorithm in maze solving problems.
Keywords :
biology; feedback; fuzzy logic; microorganisms; path planning; Physarum polycephalum; amoeboid organism; fuzzy rule; mathematical model; maze solving algorithm; positive feedback mechanism; Complexity theory; Conductivity; Electron tubes; Equations; Mathematical model; Nickel; Organisms; Fuzzy rule; Maze solving algorithm; Physarum polycephalum;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (CCDC), 2011 Chinese
Conference_Location :
Mianyang
Print_ISBN :
978-1-4244-8737-0
Type :
conf
DOI :
10.1109/CCDC.2011.5968418
Filename :
5968418
Link To Document :
بازگشت