采用人工生命方法模拟七星瓢虫捕食行为进化

自从 2 0世纪 70年代Ｂｕｒｋｓ[1] 提出人工生命的概念后 ,人工生命作为一个全新的研究领域 ,以其特有的优势在近些年来得到迅猛地发展。人工生命的基本思想是去构造某种人工系统以达到对生物的生长、发育、遗传、变异、生殖、进化、学习等生命过程重要特征的模拟 ,从而认清这些生命现象的本质。人工生命有广泛的应用 ,它所使用的方法也是多样的。粗略地说 ,可分为湿件 (Ｗｅｔｗａｒｅ ,意为采用化学方法模拟 )、硬件 (Ｈａｒｄｗａｒｅ ,意为用机器人模拟 )和软件 (Ｓｏｆｔｗａｒｅ ,意为用程序模拟 )。本文集中在采用软件方法进行行为…

Simualtion of LadyBeetle's Preying Behavior Evolution with Neural Network and Genetic Algorithms.

This paper describes a computational model of searching behavior of lady beetle ( Coccinella septempunctata L.) by using Neural Network and Genetic Algorithms. It also describes several Neural Network structures to interpret how the Neural Network controls the behavior of lady beetle, as well as the evolution of the computational model. In the nature, Alphid's pattern is clumped, and the lady beetle 's food-foraging strategy is: when the predator does not touch the prey, the predator's behavior is searching in a large area; but if the predator finds a prey, it behavior switch to searching in the neighborhood area around the prey.In this paper, several Neural NetWork structures have been used to control the individuals' food-searching behavior. And a form of Genetic Algorithms have been used for the Neural Network's Learning.After simulation, the model 's food-foraging strategy is similar to the nature. It is not very necessary for the lady beetle to have the ability of finding the Alphid in a short distance. In fact the Alphid almost can not escape after the lady beetle finds it. So the most important factor for improving the searching efficiency is the ability of memory. It coincides with the lady beetle 's food-foraging behavior in the nature.