Self-organization of inner symbols for chase: symbol organization and embodiment
Self-organization of inner symbols for chase: symbol organization and embodiment
复制标题
追逐内在符号的自组织：符号组织与体现
DOI：
10.1109/icsmc.2004.1400021
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发表时间：
2004
期刊：
影响因子：
--
通讯作者：
T. Sawaragi
中科院分区：
文献类型：
--
作者：
T. Taniguchi;T. Sawaragi
本文提出了一种新的机器学习方法，称为轻双模式模型。双图式模型是主观符号生成的框架。轻型双模式模型是通用双模式模型的特殊版本。在机器学习研究的背景下，机器设计者和/或任务设计者决定代理学习的大多数问题。然而，在未来，他们必须找到目标概念来自己学习与环境和/或其他代理的彻底交互。我们的双模式模型使自主代理能够注意到动态环境之间的差异。这个概念的灵感来自皮亚杰的图式模型。双图式模型将认知发展模型的一部分实现为计算模型。实验作为模型的实际例子进行了展示。在这个实验中，自主面部机器人能够追踪每个球的运动，创建与环境动态相对应的符号，并识别每个运动，而无需任何教学信号。
This paper presents a new machine learning method, called light dual-schemata model. Dual-schemata model is a framework for subjective symbol generation. Light dual-schemata model is a specialized version of a general dual-schemata model. In the context of machine-learning research, machine designers and/or task designers decide most problems for an agent to learn. In the future, however, they must find target concepts to learn thorough interactions with environments and/or other agents by themselves. Our dual-schemata model gives an autonomous agent an ability to notice differences among dynamic environments. This concept is inspired by Piaget's schema model. Dual-schemata model realizes a part of this cognitive development model as computational model. An experiment is shown as an actual example of the model. In this experiment an autonomous facial robot becomes able to chase each ball movements, to create symbols corresponding to environmental dynamics, and to recognize each movement, without any teaching signals.