A Heuristic Bioinspired for 8-Piece Puzzle

2017 International Conference on Artificial Intelligence Applications and Technologies

计算机科学

MacHado, M.O.^1 ; Fabres, P.A.^1 ; Melo, J.C.L.^2

UFMS/CPAN, Brazil^1

UFRJ, Brazil^2

关键词: Computational resources;    Informed search;    Local search;    Metaheuristic;    Objective functions;    Parameterized;    Significant variables;    Work hypothesis;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/261/1/012007/pdf
DOI  :  10.1088/1757-899X/261/1/012007

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

This paper investigates a mathematical model inspired by nature, and presents a Meta-Heuristic that is efficient in improving the performance of an informed search, when using strategy A ∗ using a General Search Tree as data structure. The work hypothesis suggests that the investigated meta-heuristic is optimal in nature and may be promising in minimizing the computational resources required by an objective-based agent in solving high computational complexity problems (n-part puzzle) as well as In the optimization of objective functions for local search agents. The objective of this work is to describe qualitatively the characteristics and properties of the mathematical model investigated, correlating the main concepts of the A ∗ function with the significant variables of the metaheuristic used. The article shows that the amount of memory required to perform this search when using the metaheuristic is less than using the A ∗ function to evaluate the nodes of a general search tree for the eight-piece puzzle. It is concluded that the meta-heuristic must be parameterized according to the chosen heuristic and the level of the tree that contains the possible solutions to the chosen problem.