@article{ART002294738},
author={Kyeonah Yu and Chojung Lee and Inyoung Cho},
title={Development of a Multi-criteria Pedestrian Pathfinding Algorithm by Perceptron Learning},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2017},
volume={22},
number={12},
pages={49-54},
doi={10.9708/jksci.2017.22.12.049}
TY - JOUR
AU - Kyeonah Yu
AU - Chojung Lee
AU - Inyoung Cho
TI - Development of a Multi-criteria Pedestrian Pathfinding Algorithm by Perceptron Learning
JO - Journal of The Korea Society of Computer and Information
PY - 2017
VL - 22
IS - 12
PB - The Korean Society Of Computer And Information
SP - 49
EP - 54
SN - 1598-849X
AB - Pathfinding for pedestrians provided by various navigation programs is based on a shortest path search algorithm. There is no big difference in their guide results, which makes the path quality more important. Multiple criteria should be included in the search cost to calculate the path quality, which is called a multi-criteria pathfinding. In this paper we propose a user adaptive pathfinding algorithm in which the cost function for a multi-criteria pathfinding is defined as a weighted sum of multiple criteria and the weights are learned automatically by Perceptron learning. Weight learning is implemented in two ways: short-term weight learning that reflects weight changes in real time as the user moves and long-term weight learning that updates the weights by the average value of the entire path after completing the movement. We use the weight update method with momentum for long-term weight learning, so that learning speed is improved and the learned weight can be stabilized. The proposed method is implemented as an app and is applied to various movement situations. The results show that customized pathfinding based on user preference can be obtained.
KW - Path searching algorithm;Multi-criteria pathfinding;Perceptron learning;Customized pathfinding
DO - 10.9708/jksci.2017.22.12.049
ER -
Kyeonah Yu, Chojung Lee and Inyoung Cho. (2017). Development of a Multi-criteria Pedestrian Pathfinding Algorithm by Perceptron Learning. Journal of The Korea Society of Computer and Information, 22(12), 49-54.
Kyeonah Yu, Chojung Lee and Inyoung Cho. 2017, "Development of a Multi-criteria Pedestrian Pathfinding Algorithm by Perceptron Learning", Journal of The Korea Society of Computer and Information, vol.22, no.12 pp.49-54. Available from: doi:10.9708/jksci.2017.22.12.049
Kyeonah Yu, Chojung Lee, Inyoung Cho "Development of a Multi-criteria Pedestrian Pathfinding Algorithm by Perceptron Learning" Journal of The Korea Society of Computer and Information 22.12 pp.49-54 (2017) : 49.
Kyeonah Yu, Chojung Lee, Inyoung Cho. Development of a Multi-criteria Pedestrian Pathfinding Algorithm by Perceptron Learning. 2017; 22(12), 49-54. Available from: doi:10.9708/jksci.2017.22.12.049
Kyeonah Yu, Chojung Lee and Inyoung Cho. "Development of a Multi-criteria Pedestrian Pathfinding Algorithm by Perceptron Learning" Journal of The Korea Society of Computer and Information 22, no.12 (2017) : 49-54.doi: 10.9708/jksci.2017.22.12.049
Kyeonah Yu; Chojung Lee; Inyoung Cho. Development of a Multi-criteria Pedestrian Pathfinding Algorithm by Perceptron Learning. Journal of The Korea Society of Computer and Information, 22(12), 49-54. doi: 10.9708/jksci.2017.22.12.049
Kyeonah Yu; Chojung Lee; Inyoung Cho. Development of a Multi-criteria Pedestrian Pathfinding Algorithm by Perceptron Learning. Journal of The Korea Society of Computer and Information. 2017; 22(12) 49-54. doi: 10.9708/jksci.2017.22.12.049
Kyeonah Yu, Chojung Lee, Inyoung Cho. Development of a Multi-criteria Pedestrian Pathfinding Algorithm by Perceptron Learning. 2017; 22(12), 49-54. Available from: doi:10.9708/jksci.2017.22.12.049
Kyeonah Yu, Chojung Lee and Inyoung Cho. "Development of a Multi-criteria Pedestrian Pathfinding Algorithm by Perceptron Learning" Journal of The Korea Society of Computer and Information 22, no.12 (2017) : 49-54.doi: 10.9708/jksci.2017.22.12.049
