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On the design of neuro-controllers for individual and social learning behaviour in autonomous robots: an evolutionary approach

机译:关于自主机器人个人和社交学习行为的神经控制器的设计:一种进化方法

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In biology/psychology, the capability of natural organisms to learn from the observation/interaction with conspecifics is referred to as social learning. Roboticists have recently developed an interest in social learning, since it might represent an effective strategy to enhance the adaptivity of a team of autonomous robots. In this study, we show that a methodological approach based on artifcial neural networks shaped by evolutionary computation techniques can be successfully employed to synthesise the individual and social learning mechanisms for robots required to learn a desired action (i.e. phototaxis or antiphototaxis).
机译:在生物学/心理学中,自然生物从与物种的观察/相互作用中学习的能力被称为社会学习。机器人专家最近对社交学习产生了兴趣,因为它可能代表一种增强自主机器人团队适应性的有效策略。在这项研究中,我们表明,基于由进化计算技术形成的人工神经网络的方法学方法可以成功地用于合成学习所需动作(即趋光性或反趋光性)所需的机器人的个体和社会学习机制。

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