Adaptive Representation: A Moderate Stance on Predictive Processing

Zhichao Gong; Yidong Wei

doi:doi:10.11648/j.ss.20251402.12

Research Article |

| Peer-Reviewed

Adaptive Representation: A Moderate Stance on Predictive Processing

Zhichao Gong

, Yidong Wei^*

Published in Social Sciences (Volume 14, Issue 2)

Received: 27 April 2024 Accepted: 13 May 2024 Published: 11 March 2025

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

Predictive processing (PP), emerging as a novel research paradigm in contemporary cognitive science, offers a departure from both traditional computational representation views and 4E+S cognition perspectives. This theory advocates that the brain is a hierarchical prediction model based on Bayesian inference, which aims to minimize the difference between the predicted world and the actual world to prediction error minimization. In recent years, the problem of representation has emerged as a focal point in the philosophical examination of PP. This article introduces two primary strands of PP theories: conservative predictive processing (CPP) and radical predictive processing (RPP). Building upon these frameworks, it outlines three distinct positions regarding the representation problem within PP: representationalism, anti-representationalism, and a moderate stance on representations. Lastly, the article proposes a new perspective on representation: Adaptive Representation. Adaptive representation highlights the fact that generative processes are adaptive processes, and that adaptation is not necessarily optimal, whether based on natural selection or natural drift; and that generation is at the same time a representational process. By advocating for a form of weak representationalism grounded in adaptive processes, this perspective supports a moderate stance on representations within PP.

Published in	Social Sciences (Volume 14, Issue 2)
DOI	10.11648/j.ss.20251402.12
Page(s)	78-86
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2025. Published by Science Publishing Group

Keywords

Predictive Processing, Adaptive Representation, Representationalism, Anti-representationalism, Structural Representation

References

[1]	Clark A. Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behavioral and brain sciences, 2013, 36(3), 181-204. https://doi.org/10.1017/S0140525X12000477
[2]	Hohwy J. The predictive mind. Oxford: OUP; 2013, pp. 2-3.
[3]	Clark A. Radical predictive processing. The Southern Journal of Philosophy, 2015, 53, 3-27. https://doi.org/10.1111/sjp.12120
[4]	Constant A, Clark A, Friston K J. Representation wars: Enacting an armistice through active inference. Frontiers in Psychology, 2021, 11, 598733. https://doi.org/10.3389/fpsyg.2020.598733
[5]	Christias D. Contentless Representationalism? A Neglected Option Between Radical Enactivist and Predictive Processing Accounts of Representation. Minds and Machines, 2024, 34(1), 1-21. https://doi.org/10.1007/s11023-024-09659-z
[6]	Gładziejewski, P. Predictive coding and representationalism. Synthese, 2016, 193, 559-582. https://doi.org/10.1007/s11229-015-0762-9
[7]	Gładziejewski P, Miłkowski M. Structural representations: Causally relevant and different from detectors. Biology & philosophy, 2017, 32, 337-355. https://doi.org/10.1007/s10539-017-9562-6
[8]	Downey A. Predictive processing and the representation wars: A victory for the eliminativist (via fictionalism). Synthese, 2018, 195, 5115-5139. https://doi.org/10.1007/s11229-017-1442-8
[9]	van Es T, Myin E. Predictive processing and representation: How less can be more. The philosophy and science of predictive processing, 2020, 7, 1-23.
[10]	Facchin M. Predictive processing and anti-representationalism. Synthese, 2021, 199(3), 11609-11642. https://doi.org/10.1007/s11229-021-03304-3
[11]	Ramsey W M. Representation reconsidered. Cambridge: CUP; 2007, pp. 24-33.
[12]	Dołega, K. Moderate predictive processing. In Philosophy and predictive processing, Metzinger, T., Wiese, W., Ed., MIND Group: Frankfurt am Main; 2017, pp. 1-19.
[13]	Clark A. Predicting peace: The end of the representation wars. In Open MIND: 7(R), Metzinger, T., Windt, J, M., Ed., MIND Group: Frankfurt am Main; 2015, pp. 1-7.
[14]	Helmholtz H. Handbuch der Physiologischen Optik: Vol. 3. New York: Dover; 1867, pp. 427-557.
[15]	Zhu Linfan., & Liu Chuang. A Comparative Research On Three Models of Predictive Processing. Philosophical Analysis, 2022, 13(5), 151-165+199. [朱林蕃, 刘闯. 预测心智的三种理论模型: 一个比较性研究. 哲学分析, 2022, 13(5): 151-165+199]. https://doi.org/CNKI:SUN:ZXFX.0.2022-05-012
[16]	Friston, K. The free-energy principle: a unified brain theory? Nature reviews neuroscience, 2010, 11(2), 127-138. https://doi.org/10.1038/nrn2787
[17]	Hohwy J. The self‐evidencing brain. Noûs, 2016, 50(2), 259-285. https://doi.org/10.1111/nous.12062
[18]	Merleau-Ponty M, Landes D, Carman T, et al. Phenomenology of perception. London: Routledge; 2013.
[19]	Ramsey W. Untangling two questions about mental representation. New Ideas in Psychology, 2016, 40, 3-12. https://doi.org/10.1016/j.newideapsych.2015.01.004
[20]	Piekarski, M. Representations, direct perception, and scientific realism. In defence of conservative predictive processing [Preprint]. PhilSci-Archive, 2019, 1-25. https://philsci-archive.pitt.edu/id/eprint/16384
[21]	Shea N. VI—exploitable isomorphism and structural representation//Proceedings of the Aristotelian Society. Oxford, UK: Oxford University Press; 2014, 114(2_pt_2), 123-144.
[22]	Ramsey, W. Representation reconsidered. Cambridge: Cambridge University Press; 2009, pp. 120-166.
[23]	Orlandi N. Bayesian perception is ecological perception. Philosophical Topics, 2016, 44(2), 327-352. https://www.jstor.org/stable/26529415
[24]	Clark A. Surfing uncertainty: Prediction, action, and the embodied mind. Oxford: Oxford University Press; 2015, pp. 117-132+293.
[25]	Orlandi, N. Embedded seeing: Vision in the natural world. Noûs, 2013, 47(4), 727–747. https://www.jstor.org/stable/43828853
[26]	Orlandi, N. The innocent eye: Why vision is not a cognitive process. Oxford: Oxford University Press; 2014, pp. 40-55.
[27]	Wei Yidong. Adaptive Representation: A Unified Category of Natural Cognition and Artificial Cognition. Philosophical Research, 2019, (09): 114-124. [魏屹东. 适应性表征: 架构自然认知与人工认知的统一范畴. 哲学研究, 2019, (09): 114-124]. https://doi.org/CNKI: SUN: ZXYJ.0.2019-09-014
[28]	Wei Yidong. On Adaptive Representation and Its Methodological Significance. Journal of Shanxi University (Philosophy and Social Sciences), 2022, 45(01): 21-31. [魏屹东. 论适应性表征及其方法论意义. 山西大学学报: 哲学社会科学版, 2022, 45(01): 21-31]. https://doi.org/10.13451/j.cnki.shanxi.univ(phil.soc.)
[29]	Heylighen, F. Representation and Change. A Metarepresentational Framework for the Foundations of Physical and Cognitive Science. Gent: Communication & Cognition; 1990, pp. 22-34.

Cite This Article

Plain Text BibTeX RIS

APA Style

Gong, Z., Wei, Y. (2025). Adaptive Representation: A Moderate Stance on Predictive Processing. Social Sciences, 14(2), 78-86. https://doi.org/10.11648/j.ss.20251402.12

Copy | Download

ACS Style

Gong, Z.; Wei, Y. Adaptive Representation: A Moderate Stance on Predictive Processing. Soc. Sci. 2025, 14(2), 78-86. doi: 10.11648/j.ss.20251402.12

Copy | Download

AMA Style

Gong Z, Wei Y. Adaptive Representation: A Moderate Stance on Predictive Processing. Soc Sci. 2025;14(2):78-86. doi: 10.11648/j.ss.20251402.12

Copy | Download

@article{10.11648/j.ss.20251402.12,
  author = {Zhichao Gong and Yidong Wei},
  title = {Adaptive Representation: A Moderate Stance on Predictive Processing
},
  journal = {Social Sciences},
  volume = {14},
  number = {2},
  pages = {78-86},
  doi = {10.11648/j.ss.20251402.12},
  url = {https://doi.org/10.11648/j.ss.20251402.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ss.20251402.12},
  abstract = {Predictive processing (PP), emerging as a novel research paradigm in contemporary cognitive science, offers a departure from both traditional computational representation views and 4E+S cognition perspectives. This theory advocates that the brain is a hierarchical prediction model based on Bayesian inference, which aims to minimize the difference between the predicted world and the actual world to prediction error minimization. In recent years, the problem of representation has emerged as a focal point in the philosophical examination of PP. This article introduces two primary strands of PP theories: conservative predictive processing (CPP) and radical predictive processing (RPP). Building upon these frameworks, it outlines three distinct positions regarding the representation problem within PP: representationalism, anti-representationalism, and a moderate stance on representations. Lastly, the article proposes a new perspective on representation: Adaptive Representation. Adaptive representation highlights the fact that generative processes are adaptive processes, and that adaptation is not necessarily optimal, whether based on natural selection or natural drift; and that generation is at the same time a representational process. By advocating for a form of weak representationalism grounded in adaptive processes, this perspective supports a moderate stance on representations within PP.
},
 year = {2025}
}

Copy | Download

TY  - JOUR
T1  - Adaptive Representation: A Moderate Stance on Predictive Processing

AU  - Zhichao Gong
AU  - Yidong Wei
Y1  - 2025/03/11
PY  - 2025
N1  - https://doi.org/10.11648/j.ss.20251402.12
DO  - 10.11648/j.ss.20251402.12
T2  - Social Sciences
JF  - Social Sciences
JO  - Social Sciences
SP  - 78
EP  - 86
PB  - Science Publishing Group
SN  - 2326-988X
UR  - https://doi.org/10.11648/j.ss.20251402.12
AB  - Predictive processing (PP), emerging as a novel research paradigm in contemporary cognitive science, offers a departure from both traditional computational representation views and 4E+S cognition perspectives. This theory advocates that the brain is a hierarchical prediction model based on Bayesian inference, which aims to minimize the difference between the predicted world and the actual world to prediction error minimization. In recent years, the problem of representation has emerged as a focal point in the philosophical examination of PP. This article introduces two primary strands of PP theories: conservative predictive processing (CPP) and radical predictive processing (RPP). Building upon these frameworks, it outlines three distinct positions regarding the representation problem within PP: representationalism, anti-representationalism, and a moderate stance on representations. Lastly, the article proposes a new perspective on representation: Adaptive Representation. Adaptive representation highlights the fact that generative processes are adaptive processes, and that adaptation is not necessarily optimal, whether based on natural selection or natural drift; and that generation is at the same time a representational process. By advocating for a form of weak representationalism grounded in adaptive processes, this perspective supports a moderate stance on representations within PP.

VL  - 14
IS  - 2
ER  -

Copy | Download

Author Information

Zhichao Gong

School of Philosophy, Shanxi University, Taiyuan, China; The Centre for Philosophy of Natural and Social Science, London School of Economics and Political Science, London, UK

Contact Email

http://orcid.org/0009-0005-3278-8343
Yidong Wei

School of Philosophy, Shanxi University, Taiyuan, China

Contact Email

http://orcid.org/0009-0009-2695-9416

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Gong, Z., Wei, Y. (2025). Adaptive Representation: A Moderate Stance on Predictive Processing. Social Sciences, 14(2), 78-86. https://doi.org/10.11648/j.ss.20251402.12

Copy | Download

ACS Style

Gong, Z.; Wei, Y. Adaptive Representation: A Moderate Stance on Predictive Processing. Soc. Sci. 2025, 14(2), 78-86. doi: 10.11648/j.ss.20251402.12

Copy | Download

AMA Style

Gong Z, Wei Y. Adaptive Representation: A Moderate Stance on Predictive Processing. Soc Sci. 2025;14(2):78-86. doi: 10.11648/j.ss.20251402.12

Copy | Download

@article{10.11648/j.ss.20251402.12,
  author = {Zhichao Gong and Yidong Wei},
  title = {Adaptive Representation: A Moderate Stance on Predictive Processing
},
  journal = {Social Sciences},
  volume = {14},
  number = {2},
  pages = {78-86},
  doi = {10.11648/j.ss.20251402.12},
  url = {https://doi.org/10.11648/j.ss.20251402.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ss.20251402.12},
  abstract = {Predictive processing (PP), emerging as a novel research paradigm in contemporary cognitive science, offers a departure from both traditional computational representation views and 4E+S cognition perspectives. This theory advocates that the brain is a hierarchical prediction model based on Bayesian inference, which aims to minimize the difference between the predicted world and the actual world to prediction error minimization. In recent years, the problem of representation has emerged as a focal point in the philosophical examination of PP. This article introduces two primary strands of PP theories: conservative predictive processing (CPP) and radical predictive processing (RPP). Building upon these frameworks, it outlines three distinct positions regarding the representation problem within PP: representationalism, anti-representationalism, and a moderate stance on representations. Lastly, the article proposes a new perspective on representation: Adaptive Representation. Adaptive representation highlights the fact that generative processes are adaptive processes, and that adaptation is not necessarily optimal, whether based on natural selection or natural drift; and that generation is at the same time a representational process. By advocating for a form of weak representationalism grounded in adaptive processes, this perspective supports a moderate stance on representations within PP.
},
 year = {2025}
}

Copy | Download

TY  - JOUR
T1  - Adaptive Representation: A Moderate Stance on Predictive Processing

AU  - Zhichao Gong
AU  - Yidong Wei
Y1  - 2025/03/11
PY  - 2025
N1  - https://doi.org/10.11648/j.ss.20251402.12
DO  - 10.11648/j.ss.20251402.12
T2  - Social Sciences
JF  - Social Sciences
JO  - Social Sciences
SP  - 78
EP  - 86
PB  - Science Publishing Group
SN  - 2326-988X
UR  - https://doi.org/10.11648/j.ss.20251402.12
AB  - Predictive processing (PP), emerging as a novel research paradigm in contemporary cognitive science, offers a departure from both traditional computational representation views and 4E+S cognition perspectives. This theory advocates that the brain is a hierarchical prediction model based on Bayesian inference, which aims to minimize the difference between the predicted world and the actual world to prediction error minimization. In recent years, the problem of representation has emerged as a focal point in the philosophical examination of PP. This article introduces two primary strands of PP theories: conservative predictive processing (CPP) and radical predictive processing (RPP). Building upon these frameworks, it outlines three distinct positions regarding the representation problem within PP: representationalism, anti-representationalism, and a moderate stance on representations. Lastly, the article proposes a new perspective on representation: Adaptive Representation. Adaptive representation highlights the fact that generative processes are adaptive processes, and that adaptation is not necessarily optimal, whether based on natural selection or natural drift; and that generation is at the same time a representational process. By advocating for a form of weak representationalism grounded in adaptive processes, this perspective supports a moderate stance on representations within PP.

VL  - 14
IS  - 2
ER  -

Copy | Download