Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy.
Nuffield Department of Clinical Neurosciences, University of Oxford, UK.
Biol Psychol. 2024 Feb;186:108741. doi: 10.1016/j.biopsycho.2023.108741. Epub 2024 Jan 3.
This review paper offers an overview of the history and future of active inference-a unifying perspective on action and perception. Active inference is based upon the idea that sentient behavior depends upon our brains' implicit use of internal models to predict, infer, and direct action. Our focus is upon the conceptual roots and development of this theory of (basic) sentience and does not follow a rigid chronological narrative. We trace the evolution from Helmholtzian ideas on unconscious inference, through to a contemporary understanding of action and perception. In doing so, we touch upon related perspectives, the neural underpinnings of active inference, and the opportunities for future development. Key steps in this development include the formulation of predictive coding models and related theories of neuronal message passing, the use of sequential models for planning and policy optimization, and the importance of hierarchical (temporally) deep internal (i.e., generative or world) models. Active inference has been used to account for aspects of anatomy and neurophysiology, to offer theories of psychopathology in terms of aberrant precision control, and to unify extant psychological theories. We anticipate further development in all these areas and note the exciting early work applying active inference beyond neuroscience. This suggests a future not just in biology, but in robotics, machine learning, and artificial intelligence.
这篇综述文章概述了主动推断——一种关于行动和感知的统一视角——的历史和未来。主动推断基于这样一种观点，即有感知的行为取决于我们大脑对内部模型的隐含使用，以预测、推断和指导行动。我们关注的是这个（基本）感觉理论的概念根源和发展，而不是遵循严格的时间顺序叙述。我们追溯了从赫尔姆霍茨无意识推断思想到当代对行动和感知的理解的演变。在这样做的过程中，我们触及了相关的观点、主动推断的神经基础，以及未来发展的机会。这一发展的关键步骤包括预测编码模型的制定和相关的神经元信息传递理论、用于规划和策略优化的序列模型的使用，以及分层（时间）深度内部（即生成或世界）模型的重要性。主动推断已被用于解释解剖学和神经生理学的各个方面，用异常精确控制的理论来解释精神病理学，并统一现有的心理学理论。我们预计这些领域会有进一步的发展，并注意到令人兴奋的早期工作，即将主动推断应用于神经科学以外的领域。这表明未来不仅在生物学领域，而且在机器人技术、机器学习和人工智能领域都有广阔的发展前景。
