Design and Implement of the Complex Maze Shortest Path Simulation System Based on Improved Ant Colony Optimization Algorithm

In artificial intelligence field, dynamic optimization problem under uncertain environment has always been a main topic and been widely researched these years. How to find the optimal solution around the goals to be solved is the key problem. As a typical case of uncertainty environment, maze has an important research value. In this paper we design a complex maze of random scene simulation system based on depth-first search algorithm. In the simulation system, the improved ant colony algorithm is used to find the shortest path connected maze entrance to maze exit to simulate the optimization problem in real-world. The process of how to find the shortest path dynamically of ants is displayed in this designed system and the whole behaviors of ant colony can be reflected.