面向最优化问题的人工智能搜索算法研究  

Artificial-Intelligence Search Algorithm for Optimization Problem

作　　者：王永建 杨建华 郭广涛 王治东 

机构地区：[1]中国通信建设集团设计院有限公司,北京100079

出　　处：《通信技术》2016年第11期1459-1465,共7页Communications Technology

摘　　要：搜索是人工智能领域的关键技术,随着信息技术的不断发展与成熟,人工智能未来发展前景宽广。现实中,许多问题解决的实质就是最优化过程。首先介绍最优化的概念,从解答最优化问题出发,分析动态规划算法在解决最优化问题的特殊作用。然后,分析基本搜索算法中典型的深度搜索算法和广度搜索算法的特点以及适用场景。最后,搭建仿真环境,进行对比测试。结果表明,动态规划算法的时间复杂度远小于搜索算法,但是其空间复杂度远大于搜索算法,二者适用于不同的场景。Search is the key technology in the field of artificial intelligence. With the ripid development and mature of information technologies, artificial intelligence would have a broad development prospects in the future. The essence for solving many problems, in fact, is the process of optimization. Firstly, the concept of optimization is described, and then from the solution to optimization problem, the special functions of dynamic programming algorithm in solving optimization problem are analyzed. And then the typical depth search algorithm and breadth search algorithm in basic search algorithms are discussed, including their applicable environments. Finally, the simulation environment is built up and the contrast test is done, and the results show that the time complexity of dynamic programming algorithm is much less than that of search algorithm, but the space complexity is much larger than that of search algorithm, and these two algorithms are suitable for different scenarios. As the ascendant field, artificial intelligence requires continuous research and exploration.

关 键 词：人工智能 最优化 动态规划 深度搜索 广度搜索 

分 类 号：TP392[自动化与计算机技术—计算机应用技术]