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Perception and prediction — A connectionist model

机译:感知和预测—联结主义模型

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摘要

Generating appropriate responses to incoming stimuli is a fundamental task of an organism. However, in order to generate intelligent responses, it is important to have a deeper understanding of the environment, and make predictions based on this knowledge. Although the ability to make predictions is intrinsic in humans and many animals, it is still a difficult task for a machine with no in built knowledge about the situation. In this paper we present a biologically inspired neural network model that predicts the future trajectory of a moving object after observing its current trajectory.
机译:对传入的刺激产生适当的反应是有机体的基本任务。但是,为了生成智能响应,对环境进行更深入的了解并基于此知识进行预测非常重要。尽管做出预测的能力是人类和许多动物所固有的,但是对于一台不具备有关情况的内置知识的机器而言,这仍然是一项艰巨的任务。在本文中,我们提出了一种受生物启发的神经网络模型,该模型在观察运动对象的当前轨迹后预测其运动轨迹。

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