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一种基于操作条件反射原理的学习模型 被引量：4

A learning model based on operant conditioning principles
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摘要 针对认知机器人的自主学习问题,提出一种基于操作条件反射原理的学习模型(OCLM).该模型采用状态空间、操作行为空间、概率分布函数、仿生学习机制、系统熵等进行描述,给出状态的"负理想度"的概念,定义了取向函数的计算方法.运用模型对机器人避障导航问题进行仿真实验,并对参数设置进行了讨论.实验结果表明,基于OCLM模型的机器人能通过与环境的交互获得认知,成功避障到达目的地,具有一定的自学习能力,从而表明了模型的有效性. Inspired by Skinner’s operant conditioning theory, an operant conditioning learning model is presented to deal with the autonomous learning problem in cognitive robotics. The model is described by nine elements, including the space set, the action set, the bionic learning function and the system entropy etc. A notion ＂negative ideal rate＂ is defined to compute the orientation function. The OCLM is applied to solve obstacle avoidance and navigation problems for mobile robots. The experiment results show that the robot based on the model can autonomously learn how to arrive at the goal in a collision-free way through interaction with the environment, and show the effectiveness of the proposed model.
作者 阮晓钢 黄静 范青武 魏若岩
机构地区 北京工业大学电子信息与控制工程学院 北京工业大学实验学院
出处 《控制与决策》 EI CSCD 北大核心 2014年第6期1016-1020,共5页 Control and Decision
基金 国家自然科学基金项目(61075110) 北京市自然科学基金项目(KZ201210005001) 国家973计划项目(2012CB720000) 高等学校博士学科点专项科研基金项目(20101103110007)
关键词 学习模型 操作条件反射 自学习 仿生 避障 learning model operant conditioning autonomous learning bionics obstacle avoidance
分类号 TP273 [自动化与计算机技术—检测技术与自动化装置]
  • 相关文献

参考文献10

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二级参考文献23

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共引文献6

同被引文献26

  • 1沈晶,顾国昌,刘海波.分层强化学习研究综述[J].模式识别与人工智能,2005,18(5):574-581. 被引量：7
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引证文献4

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控制与决策
2014年 第6期

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