On the Timescales of Embodied Intelligence for Autonomous Adaptive Systems

IF 11.2 1区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Annual Review of Control Robotics and Autonomous Systems Pub Date : 2022-11-18 DOI:10.1146/annurev-control-063022-094301

F. Iida, F. Giardina

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引用次数: 3

Abstract

Embodiment is a crucial concept for the autonomy and adaptivity of systems working in the physical world with high degrees of uncertainty and complexity. The physical bodies of autonomous adaptive systems heavily influence the information flow from the environment to the central processing (and vice versa), requiring us to consider the full triad of brain, body, and environment to investigate intelligent behavior. This article provides a structured review of embodied intelligence with a special emphasis on the concept of timescales and their role in self-organization and the emergence of complex behavior. We classify embodied interactions into three types—cross-timescale matching, separation, and nontemporal sequences—and discuss how these interactions were studied in the past as well as how they can contribute to the systematic investigation of complex autonomous and adaptive systems in both biological and artificial entities. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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自主适应系统具身智能的时间尺度研究

具体化是在具有高度不确定性和复杂性的物理世界中工作的系统的自主性和适应性的关键概念。自主适应系统的物理实体严重影响从环境到中央处理的信息流(反之亦然)，要求我们考虑大脑，身体和环境的完整三合一来研究智能行为。本文对具身智力进行了结构化的回顾，特别强调了时间尺度的概念及其在自组织和复杂行为出现中的作用。我们将具体的相互作用分为三种类型——跨时间尺度匹配、分离和非时间序列，并讨论了这些相互作用在过去是如何被研究的，以及它们如何有助于对生物和人工实体中复杂的自主和自适应系统的系统研究。预计《控制、机器人和自主系统年度评论》第14卷的最终在线出版日期是2023年5月。修订后的估计数请参阅http://www.annualreviews.org/page/journal/pubdates。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Annual Review of Control Robotics and Autonomous Systems Multiple-

CiteScore

28.30

自引率

2.20%

发文量

期刊介绍： The Annual Review of Control, Robotics, and Autonomous Systems offers comprehensive reviews on theoretical and applied developments influencing autonomous and semiautonomous systems engineering. Major areas covered include control, robotics, mechanics, optimization, communication, information theory, machine learning, computing, and signal processing. The journal extends its reach beyond engineering to intersect with fields like biology, neuroscience, and human behavioral sciences. The current volume has transitioned to open access through the Subscribe to Open program, with all articles published under a CC BY license.