卡尔·弗里斯顿：我和我的马尔可夫毯：能动推理和最小自由能原理

中国科学院哲学研究所（CASIP）和复旦大学智能科学与智能哲学研究中心（Fudan PSI）将于2022年9月30日联合邀请著名理论神经科学家卡尔·弗里斯顿（Karl Friston）作报告。弗里斯顿教授是英国伦敦大学学院神经学学院维康信托基金会神经影像中心的科学主任，也是脑成像领域的权威。他还是北京智源人工智能研究院学术顾问。弗里斯顿教授的重要贡献是以自由能原理为理解大脑提供了一个统一框架，他将在本次讲座中介绍他对最小自由能原理与能动推理的思考。《返朴》将在微信视频号、新浪微博和B站提供独家直播。【前往“返朴”公众号可预约直播】

CASIP与Fudan PSI讲座

我和我的马尔可夫毯：能动推理和最小自由能原理

主讲人：Karl J. Friston（伦敦大学学院）

主持人：刘闯（复旦大学/中国科学院哲学研究所）

评论人：

吴东颖（中国科学院哲学研究所）

韦南昕（帝国理工学院）

徐英瑾（复旦大学）

Deniz Vatansever（复旦大学）

时间：2022年9月30日 19:00-21:00 （北京时间）

讲座工作语言为英语

主办单位：

中国科学院哲学研究所（CASIP）

复旦大学智能科学与智能哲学研究中心（PSI中心）

讲座摘要

我们如何能理解作为有知觉生物的我们自己？在知觉行为之下隐藏的原则是什么？本报告将用最小自由能原理在能动推理方面作出说明。首先，我们将从物理的角度试图去理解知觉，即将其本身与所处的环境区别开来的自组织系统的属性必须存在。接下来我们从神经生物学家的角度重新叙述这一个故事，试图去理解大脑的功能结构。故事将从一个启发式的证明（和对原始汤的模拟）开始，它（们）揭示了生命，或者称之为生物学自组织，是具有马尔可夫毯的任何动力学系统所具有的必然的涌现性质。这个结论基于以下论证：如果一个系统可以与它的环境背景区别开来，它的内部状态和外部状态必然是条件独立的。这样的独立性导出区分内部状态和外部状态的马尔可夫毯。关键在于，这给予了内部状态以一种信息几何学，适用于对被称为外界状态的概率信念。这种自由能也是在贝叶斯推理和机器学习中被最优化的量（在机器学习中被称为证据下界（ELBO））。简而言之，内部状态会表现出推断外部世界并行动作用于外部世界以保持其完整性。这导出了一种贝叶斯机制，它可以简洁地被总结为自证性。在报告的第二部分，我们将会用模拟大脑中的贝叶斯信念更新来剖析这些概念并将它们与预测处理和知觉行为联系起来。

主讲人简介

卡尔·弗里斯顿（Karl Friston）是一位理论神经科学家，也是脑成像领域的权威。他发明了统计参数映射(SPM)、基于体素的形态测量 (VBM) 和动态因果建模 (DCM)。这些贡献源于对精神分裂症研究和被表述为精神分裂症的失联假说的价值学习理论的研究。数学贡献包括变分拉普拉斯程序和分层贝叶斯模型反演的广义滤波。弗里斯顿目前致力于人脑功能整合模型和神经元相互作用的基本原理。他对理论神经生物学的主要贡献是行动和感知的自由能原理（能动推理）。1996年，弗里斯顿获得了首届人脑图谱青年研究者奖，并于1999 年被选为英国医学科学院院士。2000年，他担任国际人脑图谱组织主席。2003年，他被授予密涅瓦金脑奖，并于 2006年被选为皇家学会会员。2008年，他获得了法兰西学院奖章，并于2011年获得约克大学的荣誉博士学位。他于2012年成为英国皇家生物学会院士，2013年因对数学生物学的贡献获得韦尔登纪念奖和奖章，并于2014年当选为EMBO（生命科学卓越）成员，2015年当选为欧洲学术界成员。2016年，他因在脑研究方面的无与伦比的突破而获得查尔斯·布兰奇奖，并获得人类脑图谱领域的终身成就奖——玻璃脑奖。他拥有苏黎世大学和拉德布德大学的荣誉博士学位。

图片来源：
https://www.wired.com/story/karl-friston-free-energy-principle-artificial-intelligence/

CASIP and Fudan PSI International Lecture

Me and My Markov Blanket: Active Inference and the Free Energy Princip

Speaker: Karl J. Friston (University College London)

Chair: Chuang Liu (Fudan University/ CASIP)

Commentators:

Tung-Ying Wu (CASIP)

Nanxin Wei (Imperial College London)

Yingjin Xu (Fudan University)

Deniz Vatansever (Fudan University)

Time: Friday, 30th September, 2022, 7:00 PM—9:00 PM (UTC+8)

Language: English

Organizer:

Institute of Philosophy, Chinese Academy of Sciences (CASIP)

The Philosophy and Science of Intelligence Center (PSI), Fudan University

Abstract

How can we understand ourselves as sentient creatures? And what are the principles that underwrite sentient behaviour? This presentation uses the free energy principle to furnish an account in terms of active inference. First, we will try to understand sentience from the point of view of physics; in particular, the properties that self-organising systems--that distinguish themselves from their lived world--must possess. We then rehearse the same story from the point of view of a neurobiologist, trying to understand functional brain architectures. The narrative starts with a heuristic proof (and simulations of a primordial soup) suggesting that life--or biological self-organization--is an inevitable and emergent property of any dynamical system that possesses a Markov blanket. This conclusion is based on the following arguments: if a system can be differentiated from its external milieu, then its internal and external states must be conditionally independent. These independencies induce a Markov blanket that separates internal and external states. Crucially, this equips internal states with an information geometry, pertaining to probabilistic beliefs about something; namely external states. This free energy is the same quantity that is optimized in Bayesian inference and machine learning (where it is known as an evidence lower bound). In short, internal states will appear to infer--and act on--their world to preserve their integrity. This leads to a Bayesian mechanics, which can be neatly summarised as self-evidencing. In the second half of the talk, we will unpack these ideas using simulations of Bayesian belief updating in the brain and relate them to predictive processing and sentient behaviour.

Biography

Karl Friston is a theoretical neuroscientist and authority on brain imaging. He invented statistical parametric mapping (SPM), voxel-based morphometry (VBM) and dynamic causal modelling (DCM). These contributions were motivated by schizophrenia research and theoretical studies of value-learning, formulated as the dysconnection hypothesis of schizophrenia. Mathematical contributions include variational Laplacian procedures and generalized filtering for hierarchical Bayesian model inversion. Friston currently works on models of functional integration in the human brain and the principles that underlie neuronal interactions. His main contribution to theoretical neurobiology is a free-energy principle for action and perception (active inference). Friston received the first Young Investigators Award in Human Brain Mapping (1996) and was elected a Fellow of the Academy of Medical Sciences (1999). In 2000 he was President of the international Organization of Human Brain Mapping. In 2003 he was awarded the Minerva Golden Brain Award and was elected a Fellow of the Royal Society in 2006. In 2008 he received a Medal, College de France and an Honorary Doctorate from the University of York in 2011. He became of Fellow of the Royal Society of Biology in 2012, received the Weldon Memorial prize and Medal in 2013 for contributions to mathematical biology and was elected as a member of EMBO (excellence in the life sciences) in 2014 and the Academia Europaea in (2015). He was the 2016 recipient of the Charles Branch Award for unparalleled breakthroughs in Brain Research and the Glass Brain Award, a lifetime achievement award in the field of human brain mapping. He holds Honorary Doctorates from the University of Zurich and Radboud University.

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