Integrating case-based reasoning, knowledge-based approach and Dijkstra algorithm for route finding

Abstract

Imagine you rent a car and plan to drive around an unfamiliar city. Before you go from one place to another, you need to know a good route. In Network Theory (NT), this is the shortest path problem. Dijkstra's algorithm is often used for solving this problem. However, when the road network of the city is very complicated and dense, which is usually the case, it will take too long for the algorithm to find the shortest path. Furthermore, in reality, things are not as simple as those stated in NT. For instance, the cost of travel for the same part of the city at different times may not be the same. In this project, we have integrated Dijkstra's algorithm with AI knowledge-based approach and case-based reasoning in solving the problem. With this integration, knowledge about the geographical information and past cases are used to help Dijkstra's algorithm in finding a solution. This approach dramatically reduces the computation time required for route finding. A prototype system has been implemented for route finding in Singapore.