Sensorimotor Prediction with Neural Networks on Continuous Spaces

被引：0
|
作者：
Ortiz, Michael Garcia [1 ]
机构：
[1] SoftBank Robot Europe AI Lab, 43 Rue Colonel Pierre Avia, F-75015 Paris, France
来源：
ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING - ICANN 2017, PT I | 2017年 / 10613卷
关键词：
D O I：
10.1007/978-3-319-68600-4_10
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In the context of Developmental Robotics, we propose to learn how the sensations of a robot are modified by its action. Many theories of Artificial Intelligence argue that sensorimotor prediction is a fundamental building block of cognition. In this paper, we learn the sensorimotor prediction on data captured by a mobile robot equipped with distance sensors. We show that Neural Networks can learn the sensorimotor regularities and perform sensorimotor prediction on continuous sensor and motor spaces.
引用
收藏
页码：76 / 83
页数：8
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