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The Effect of Noise on the Performance of Cultural Evolution in Multi-Agent Systems

机译:噪声对多助理系统中文化演化性能的影响

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This paper examines the effect of the addition of noise to the cultural learning process of a population of agents. Experiments are undertaken using an artificial life simulator capable of simulating population learning (through the use of genetic algorithms) and lifetime learning (through the use of neural networks). To simulate cultural learning, (the exchange of information through non-genetic means) a group of highly fit agents is selected at each generation to function as teachers which are assigned a number of pupils to instruct. Cultural exchanges occur through a hidden layer of an agent's neural network known as the verbal layer. Through the use of back-propagation, a pupil agent imitates the teacher's behaviour and overall population fitness is increased. We introduce cultural mutation into a population of agents by adding noise to cultural exchanges between teacher and pupil agents. We conduct a series of experiments with varying values of cultural mutation to study the effects of this operator on the performance of the population. We show that the addition of noise to cultural exchanges can improve on the performance of cultural learning.
机译:本文研究了噪声对代理人群体的文化学习过程的影响。使用能够模拟人口学习(通过使用遗传算法)和寿命学习(通过使用神经网络)的人工生命模拟器进行实验。为了模拟文化学习,(通过非遗传手段交流信息)在各一代中选择了一组高度适合的药剂,以担任教师,这些教师被分配了一些学生的指导。文化交流通过被称为口头图层的代理人神经网络的隐藏层进行。通过使用背部传播,瞳孔代理模仿教师的行为,总体人口适合增加。通过向教师和学生代理商之间的文化交流添加噪音,将文化突变介绍为代理人群体。我们开展一系列实验,具有不同的文化突变值,以研究该操作员对人口表现的影响。我们表明对文化交流的噪音增加可以改善文化学习的表现。

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