Developing Hierarchical Schemas and Building Schema Chains Through Practice Play Behavior.

Developing Hierarchical Schemas and Building Schema Chains Through Practice Play Behavior.
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DOI:
10.3389/fnbot.2018.00033
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发表时间:
2018
影响因子:
3.1
通讯作者:
Shen Q
Shen Q
中科院分区:
计算机科学3区
文献类型:
--
作者:
Kumar S;Shaw P;Giagkos A;Braud R;Lee M;Shen Q

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研究人类早期通过游戏学习的不同阶段一直是各个学者感兴趣的话题。游戏从实践到象征性,再到后来的游戏规则。在实践游戏中,婴儿在与周围物体互动的同时经历了一个发展知识的过程,有助于创造关于物体的新知识和与物体相关的行为。这种知识被用来形成图式,在图式中捕捉到感觉运动经验的表现。通过后续的操作,将进一步组合某些模式,以生成能够实现需要多个步骤的行为的链。图式链演示了层次结构中更高级别的操作的形成。在这项工作中,我们提出了一个基于模式的人工代理游戏生成器,称为Dev-PSchema。在模拟环境和iCub机器人实验的帮助下,我们演示了我们的系统能够从与环境的嬉戏互动中创建感知运动体验的模式。我们展示了由一系列操作组成的架构链的创建,这些操作允许代理自主执行复杂的任务。除了演示通过玩耍行为学习的能力外,我们还演示了Dev-PSchema模拟不同婴儿对新对象和熟悉对象的不同偏好的能力。
Examining the different stages of learning through play in humans during early life has been a topic of interest for various scholars. Play evolves from practice to symbolic and then later to play with rules. During practice play, infants go through a process of developing knowledge while they interact with the surrounding objects, facilitating the creation of new knowledge about objects and object related behaviors. Such knowledge is used to form schemas in which the manifestation of sensorimotor experiences is captured. Through subsequent play, certain schemas are further combined to generate chains able to achieve behaviors that require multiple steps. The chains of schemas demonstrate the formation of higher level actions in a hierarchical structure. In this work we present a schema-based play generator for artificial agents, termed Dev-PSchema. With the help of experiments in a simulated environment and with the iCub robot, we demonstrate the ability of our system to create schemas of sensorimotor experiences from playful interaction with the environment. We show the creation of schema chains consisting of a sequence of actions that allow an agent to autonomously perform complex tasks. In addition to demonstrating the ability to learn through playful behavior, we demonstrate the capability of Dev-PSchema to simulate different infants with different preferences toward novel vs. familiar objects.
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