首页> 外文会议>Connectionist models of neurocognition and emergent behavior : From theory to applications >A FIRST APPROACH TO AN ARTIFICIAL NETWORKED COGNITIVE CONTROL SYSTEM BASED ON THE SHARE! CIRCUITS MODEL OF SOCIOCOGNITIVE CAPACITIES
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A FIRST APPROACH TO AN ARTIFICIAL NETWORKED COGNITIVE CONTROL SYSTEM BASED ON THE SHARE! CIRCUITS MODEL OF SOCIOCOGNITIVE CAPACITIES

机译:基于共享的人工网络认知控制系统的第一种方法!社会认知能力的电路模型

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摘要

The top priority in high-performance manufacturing processes is the development of a new generation of control systems to enable faster, more efficient manufacturing by means of cooperative, self-organized, self-optimized behaviour. Some natural cognitive systems display effective behaviour through perception, action, deliberation, communication, and interaction with other individuals and with the environment. An artificial cognitive control architecture is presented which is based on the shared circuits model (SCM) of sociocognitive skills proposed by Hurley.1 The proposal consists of a five-layer architecture in which the SCM approach is used to emulate such sociocognitive skills as imitation, deliberation, and mindreading. In Hurley's approach, these capacities can be enabled by mechanisms of control, mirroring the actions of others, and simulation. A control system thus designed should be capable of responding efficiently and robustly to the problems it is set. In the present implementation, the original SCM approach was enriched and modified in the light of constructive suggestions and evaluations in the literature. With these modifications, SCM served as the foundation for the design of a networked control architecture for application to an industrial case study - a high-performance drilling process. Experiments demonstrated that the proposed artificial cognitive control system can deal with nonlinearities and uncertainties in the drilling process, providing a good transient response and good error-based performance indices.
机译:高性能制造过程中的重中之重是开发新一代控制系统,以通过协作,自组织,自优化的行为实现更快,更高效的制造。一些自然的认知系统通过感知,行动,协商,沟通以及与其他个体和环境的互动来显示有效的行为。提出了一种人工认知控制架构,该架构基于Hurley提出的社交认知技能的共享电路模型(SCM)。1该提案由五层架构组成,其中SCM方法用于模仿诸如模仿,商量和思考。在Hurley的方法中,可以通过控制机制,镜像其他人的行为以及模拟来启用这些功能。这样设计的控制系统应该能够有效,可靠地响应所设置的问题。在当前的实现中,原始的SCM方法根据文献中的建设性建议和评估进行了丰富和修改。经过这些修改,SCM成为了设计用于工业案例研究(一种高性能钻井过程)的网络控制体系结构的基础。实验表明,所提出的人工认知控制系统可以处理钻井过程中的非线性和不确定性,具有良好的瞬态响应和基于误差的良好性能指标。

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  • 来源
  • 会议地点 Birkbeck(GB);Birkbeck(GB)
  • 作者单位

    Centre for Automation and Robotics, Spanish National Research Council,Ctra. Campo Real km. 0,200, Arganda del Rey, Madrid 28500, Spain;

    Centre for Automation and Robotics, Spanish National Research Council,Ctra. Campo Real km. 0,200, Arganda del Rey, Madrid 28500, Spain,Escuela Politecnica Superior, Universidad Autonoma de Madrid,Calle Francisco Tomds y Valiente 11, Madrid 2804-9, Spain;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 心理学;
  • 关键词

  • 入库时间 2022-08-26 14:11:22

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