arXiv:2412.00748cs.AI2024-12被引 1

从形态计算视角重新定义认知,揭示生物体的物质结构本身具有计算能力。

Exploring Cognition through Morphological Info-Computational Framework

  • 将自然结构视为信息,其变化过程视为计算,构建认知的非符号化框架。
  • 强调认知依赖观察者视角,物质基底的形态变化即为计算行为。
  • 适合对具身智能、演化认知和生物启发式AI感兴趣的学者。

传统上,认知被视为人类独有的能力,包括感知、记忆、学习、推理与问题解决。然而,最新研究显示,认知是所有生命体共有的基本能力,从单细胞到复杂生物皆具备。本章采用信息-计算框架(ICON),将自然结构视为信息,其变化过程视为计算。该框架依赖于认知者的观察视角,信息结构是物质基底的属性;关注基底行为时,即进入形态计算(MC)范畴。ICON与MC互为补充,信息、计算与认知密不可分。本文探讨了自然作为认知者眼中计算结构的研究,涵盖形态计算、形态发生、代理性、延伸认知及延伸进化综合理论,并以自由能原理与主动推断为例。提出挑战传统抽象符号处理模型的理论与实践路径,突出物质基底固有的计算能力(具身性)。理解认知的具身性及其形态计算基础,对生物学、演化、智能理论、人工智能与机器人学等领域至关重要。

原文摘要 · Abstract (English)

Traditionally, cognition has been considered a uniquely human capability involving perception, memory, learning, reasoning, and problem-solving. However, recent research shows that cognition is a fundamental ability shared by all living beings, from single cells to complex organisms. This chapter takes an info-computational approach (ICON), viewing natural structures as information and the processes of change in these structures as computations. It is a relational framework dependent on the perspective of a cognizing observer/cognizer. Informational structures are properties of the material substrate, and when focusing on the behavior of the substrate, we discuss morphological computing (MC). ICON and MC are complementary perspectives for a cognizer. Information and computation are inseparably connected with cognition. This chapter explores research connecting nature as a computational structure for a cognizer, with morphological computation, morphogenesis, agency, extended cognition, and extended evolutionary synthesis, using examples of the free energy principle and active inference. It introduces theoretical and practical approaches challenging traditional computational models of cognition limited to abstract symbol processing, highlighting the computational capacities inherent in the material substrate (embodiment). Understanding the embodiment of cognition through its morphological computational basis is crucial for biology, evolution, intelligence theory, AI, robotics, and other fields.

认知科学形态计算具身智能演化理论

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