A New Approach in Agent Path-Finding using State Mark Gradients

Since searching is one of the most important problem-solving methods, especially in Artificial Intelligence where it is often difficult to devise straightforward solutions, it has been given continuous attention by researchers. In this paper a new algorithm for agent path-finding is presented. Our a...

Full description

Bibliographic Details
Main Authors: Florin Leon, Mihai Horia Zaharia, Dan Galea
Format: Article
Language:English
Published: Institute of Mathematics and Computer Science of the Academy of Sciences of Moldova 2005-01-01
Series:Computer Science Journal of Moldova
Subjects:
Online Access:http://www.math.md/files/csjm/v12-n3/v12-n3-(pp406-423).pdf
Description
Summary:Since searching is one of the most important problem-solving methods, especially in Artificial Intelligence where it is often difficult to devise straightforward solutions, it has been given continuous attention by researchers. In this paper a new algorithm for agent path-finding is presented. Our approach is based on environment marking during exploration. We tested the performances of Q-learning and Learning Real-Time A* algorithm for three proposed mazes and then a comparison was made between our algorithm, two variants of Q-learning and LRTA* algorithm.
ISSN:1561-4042