将弱整合信息理论分为启发性方法和理想性方法。
Separating weak integrated information theory into inspired and aspirational approaches.
作者信息
Leung Angus, Tsuchiya Naotsugu
机构信息
School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Wellington Road, Clayton, VIC 3800, Australia.
Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology (NICT), 1-4 Yamadaoka, Suita-shi, Osaka 565-0871, Japan.
出版信息
Neurosci Conscious. 2023 May 17;2023(1):niad012. doi: 10.1093/nc/niad012. eCollection 2023.
Mediano et al. (The strength of weak integrated information theory. 2022;: 646-55.) separate out strong and weak flavours of the integrated information theory (IIT) of consciousness. They describe 'strong IIT' as attempting to derive a universal formula for consciousness and 'weak IIT' as searching for empirically measurable correlates of aspects of consciousness. We put forward that their overall notion of 'weak IIT' may be too weak. Rather, it should be separated out to distinguish 'aspirational-IIT', which aims to empirically test IIT by making trade-offs to its proposed measures, and 'IIT-inspired' approaches, which adopt high-level ideas of IIT while dropping the mathematical framework it reaches through its introspective, first-principles approach to consciousness.
梅迪亚诺等人（《弱整合信息理论的力量》，2022年；第646 - 55页）区分了意识整合信息理论（IIT）的强版本和弱版本。他们将“强IIT”描述为试图推导意识的通用公式，将“弱IIT”描述为寻找意识各方面的可实证测量的相关物。我们提出，他们关于“弱IIT”的总体概念可能过于薄弱。相反，应该将其区分开来，以辨别“理想IIT”，即旨在通过对其提出的测量方法进行权衡来对IIT进行实证检验，以及“受IIT启发”的方法，即采用IIT的高层次理念，同时摒弃其通过对意识的内省、第一性原理方法所达成的数学框架。
Zotero 插件