Integrating A* algorithm with neural network

Pao Yue-kong Library Electronic Theses Database

Integrating A* algorithm with neural network


Author: Lv, Ye
Title: Integrating A* algorithm with neural network
Degree: M.Sc.
Year: 2011
Subject: Neural networks (Computer science)
Computer algorithms.
Hong Kong Polytechnic University -- Dissertations
Department: Dept. of Computing
Pages: viii, 78 leaves : ill. ; 30 cm.
Language: English
InnoPac Record:
Abstract: This dissertation mainly talks the pathfinding algorithm and its relevant domain. A star algorithm is regarded the traditional and core pathfinding algorithm. There are two ways I research for improving the efficiency of the A star algorithm. One method is called block separated method; the other is using the neural network to implement the pathfinding prediction. The core idea of block separated method is to rebuild hierarchy of the map. The source map will be divided into some small blocks. Each block will be applied with the A star algorithm. Because of the characteristic of A star algorithm, small map will own high performance if the A star algorithm implements in it. The hierarchy method will give A star upgrade in efficiency. Neural network is general method for classification, pattern recognition and prediction. In pathfinding algorithm, especially A star algorithm, neural network can predict for the correction path or direction in order to decrease the cost what traditional A star algorithm spends. This study was an exercise to try to improve the traditional A star algorithm. The data source was created by a series of random number. It can affect the reliability of the result. The approach invented by me is a test or mark for the future work

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