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首页> 外文期刊>Biological Cybernetics >MODEM: a multi-agent hierarchical structure to model the human motor control system
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MODEM: a multi-agent hierarchical structure to model the human motor control system

机译:MODEM:一种多智能体层次结构,用于对人的电机控制系统进行建模

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摘要

In this study, based on behavioral and neurophysiological facts, a new hierarchical multi-agent architecture is proposed to model the human motor control system. Performance of the proposed structure is investigated by simulating the control of sit to stand movement. To develop the model, concepts of mixture of experts, modular structure, and some aspects of equilibrium point hypothesis were brought together. We have called this architecture MODularized Experts Model (MODEM). Human motor system is modeled at the joint torque level and the role of the muscles has been embedded in the function of the joint compliance characteristics. The input to the motor system, i.e., the central command, is the reciprocal command. At the lower level, there are several experts to generate the central command to control the task according to the details of the movement. The number of experts depends on the task to be performed. At the higher level, a “gate selector” block selects the suitable subordinate expert considering the context of the task. Each expert consists of a main controller and a predictor as well as several auxiliary modules. The main controller of an expert learns to control the performance of a given task by generating appropriate central commands under given conditions and/or constraints. The auxiliary modules of this expert learn to scrutinize the generated central command by the main controller. Auxiliary modules increase their intervention to correct the central command if the movement error is increased due to an external disturbance. Each auxiliary module acts autonomously and can be interpreted as an agent. Each agent is responsible for one joint and, therefore, the number of the agents of each expert is equal to the number of joints. Our results indicate that this architecture is robust against external disturbances, signal-dependent noise in sensory information, and changes in the environment. We also discuss the neurophysiological and behavioral basis of the proposed model (MODEM).
机译:在这项研究中,基于行为和神经生理学事实,提出了一种新的分层多主体体系结构,以对人体运动控制系统进行建模。通过模拟坐到站运动的控制来研究所提出结构的性能。为了开发该模型,将专家混合的概念,模块结构以及平衡点假设的某些方面综合在一起。我们称这种架构为模块化专家模型(MODEM)。人体运动系统是在关节扭矩水平上建模的,肌肉的作用已嵌入关节顺应性特征的功能中。电动机系统的输入,即中央指令,是往复指令。在较低级别,有几位专家根据运动的细节生成中央命令来控制任务。专家人数取决于要执行的任务。在较高级别,“门选择器”块会考虑任务的上下文来选择合适的下级专家。每个专家都由一个主控制器,一个预测器以及几个辅助模块组成。专家的主控制器学习通过在给定条件和/或约束条件下生成适当的中央命令来控制给定任务的执行。该专家的辅助模块学习检查主控制器生成的中央命令。如果由于外部干扰而增加了运动误差,则辅助模块会增加干预以纠正中央命令。每个辅助模块都可以自主运行,并且可以解释为代理。每个代理负责一个联合,因此,每个专家的代理人数等于联合数量。我们的结果表明,该体系结构可抵抗外部干扰,感官信息中的信号相关噪声以及环境变化。我们还讨论了所提出的模型(MODEM)的神经生理和行为基础。

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