A Path Planning Algorithm Based on Typical Case Reasoning

Case-based reasoning is an AI technique in which the previous solutions are stored for future use. People are used to guiding themselves according to those routes that are stored in their memories and have been used by them before. It is just based on people＇s preference to familiar routes, which are gained through the study of the cognitive activities. We propose to apply the intelligent method based on the case reasoning to path planning. It is impossible for a case base to store all the solutions to all the shortest paths; therefore, part of them should be stored. However, which routes should be stored and which should not be？ How do we adapt the cases that have already been stored and how do we acquire the shortest route based on them？ All these issues need to be explained by integrating knowledge of the network on account of case-based reasoning techniques. This paper suggests the case-based reasoning in another point. This means finding some irreplaceable links on the basis of the complete analysis of the problems space, which are called the must_be_passed link between the source and destination. Merely compute the shortest path case from those best exit/entry nodes of the grids to the irreplaceable links, and then add them into the case base storing for future use. This method is based on case-based reasoning technique and completely considers the properties of the problem space. In addition to the use of knowledge of the natural grid in the route network, this method is more efficient than existing algorithms on computing efficiency.

基于盒子的推理是以前的答案在被存储为未来使用的一种 AI 技术。人们习惯于根据在他们的记忆被存储并且以前被他们使用了的那些线路指导自己。只基于人到熟悉的线路的偏爱，它通过认知活动的学习被获得。我们建议基于推理到路径计划的盒子使用聪明的方法。一个盒子底存储所有答案到所有最短的路径是不可能的；因此，他们的部分应该被存储。不管多么，线路哪个并且哪个应该被存储不应该是？我们怎么并且怎么改编已经被存储了的盒子我们基于他们获得最短的线路？所有这些问题需要被由于基于盒子的推理技术，集成网络的知识解释。这篇论文建议在另一个点的基于盒子的推理。根据问题空间的总分析发现一些不能替代的连接的这个工具，它被称为 must_be_passed 在来源和目的地之间连接。仅仅从格子的那些最好的出口 / 入口节点计算最短的路径盒子到不能替代的连接，然后增加他们进存储为未来使用的盒子底。这个方法基于基于盒子的推理技术并且完全考虑问题空间的性质。除了在线路网络的自然格子的知识的使用，这个方法是比计算效率上的存在算法更有效的。