Research and Design of Artificial Intelligence Training Platform Based on Improved ant Colony Algorithm

Abstract

From the published papers, most of them still stay in the simulation stage, and few of them apply the improved ant colony algorithm to solve practical problems. With the development of business, some domestic sewage treatment plants are also actively carrying out automation transformation. So that it can give full play to its ability in the fierce market competition and achieve the best economic benefits. Robots have some sensory functions, such as sense of touch, smell and so on, which enable robots to process information of different signals autonomously. Inspired by the ant colony's foraging behavior of finding the shortest path, this paper proposes a simulated evolutionary algorithm artificial ant colony algorithm, which simulates the behavior of ant colony in nature. Ant colony algorithm has been concerned by many experts and scholars, and is being studied by more and more experts and scholars. The algorithm is continuously improved, and the application scope is more and more extensive. It is a bionic optimization algorithm with good development prospects. This paper mainly introduces the basic principle and basic model of ant colony algorithm. Finally, the improvement strategy of ant colony algorithm and the research and design of artificial intelligence training platform are discussed.