arXiv:2412.00751cs.AI2024-12被引 2

重新定义认知:生命与人工智能中的形态信息计算

Rethinking Cognition: Morphological Info-Computation and the Embodied Paradigm in Life and Artificial Intelligence

  • 将认知视为生物体在物理结构中进行的动态信息处理过程
  • 提出形态计算网络模型,涵盖自组装、自组织与自维持机制
  • 适合对具身智能、进化生物学及类脑计算感兴趣的读者

本研究旨在将Lorenzo Magnani的生态认知计算主义置于当前信息、计算与认知研究的更广阔背景下。传统观点认为认知仅属人类且源于大脑活动,但近年研究表明,它实为从单细胞到复杂多细胞生物及其网络的所有生命形式的基本特征。然而,现有文献和普遍认知仍以人脑为中心,造成概念断裂与不连贯。本文提出多种计算(信息处理)方法,包括一种信息计算认知观:自然结构承载信息,其上的动态过程被视为相对于观察认知主体的计算。我们将认知建模为由自组装、自组织与自维持驱动的并行形态计算网络,贯穿物理、化学与生物领域。探讨了形态计算、形态发生、能动性、基础认知、扩展进化综合与主动推断等最新发现之间的联系。建立与Magnani生态认知计算主义及‘无知实体的计算驯化’思想的关联。理论与应用新见解挑战了传统认知计算模型的边界。传统模型强调符号处理,常忽视代理在不同组织层次上的物理具身性约束与潜力。深化对认知具身性的信息计算理解,对生物学、进化研究、人工智能、机器人学、医学等领域的发展至关重要。

原文摘要 · Abstract (English)

This study aims to place Lorenzo Magnanis Eco-Cognitive Computationalism within the broader context of current work on information, computation, and cognition. Traditionally, cognition was believed to be exclusive to humans and a result of brain activity. However, recent studies reveal it as a fundamental characteristic of all life forms, ranging from single cells to complex multicellular organisms and their networks. Yet, the literature and general understanding of cognition still largely remain human-brain-focused, leading to conceptual gaps and incoherency. This paper presents a variety of computational (information processing) approaches, including an info-computational approach to cognition, where natural structures represent information and dynamical processes on natural structures are regarded as computation, relative to an observing cognizing agent. We model cognition as a web of concurrent morphological computations, driven by processes of self-assembly, self-organisation, and autopoiesis across physical, chemical, and biological domains. We examine recent findings linking morphological computation, morphogenesis, agency, basal cognition, extended evolutionary synthesis, and active inference. We establish a connection to Magnanis Eco-Cognitive Computationalism and the idea of computational domestication of ignorant entities. Novel theoretical and applied insights question the boundaries of conventional computational models of cognition. The traditional models prioritize symbolic processing and often neglect the inherent constraints and potentialities in the physical embodiment of agents on different levels of organization. Gaining a better info-computational grasp of cognitive embodiment is crucial for the advancement of fields such as biology, evolutionary studies, artificial intelligence, robotics, medicine, and more.

认知科学具身智能形态计算人工智能

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