Skip to main content
SpringerLink
Log in

Aligning the free-energy principle with Peirce’s logic of science and economy of research

  • Paper in History and Philosophy of Science
  • Published:
European Journal for Philosophy of Science Aims and scope Submit manuscript

Abstract

The paper proposes a way to naturalise Charles S. Peirce’s conception of the scientific method, which he specified in terms of abduction, deduction and induction. The focus is on the central issue of the economy of research in abduction and self-correction by error reduction in induction. We show how Peirce’s logic of science receives support from modern breakthroughs in computational neuroscience, and more specifically from Karl Friston’s statements of active inference and the Free Energy Principle, namely the account of how organisms’ capacity to decrease the discrepancy between the expected value and actual outcomes entails the minimisation of errors in their hypotheses about the world. A scientific account of organisms’ capacity to choose policies and form expectations is aligned with Peirce’s theories of abduction and induction, and especially with the economy of research. The upshot is the recovery of Peirce’s theory of the logic of science in the context of active inquiry.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Notes

  1. References to Peirce’s works are standard. R is to Peirce (1967) by the Robin number. CP is to Peirce (1931–1966) by volume and paragraph number. EP is to Peirce (1998).

  2. See Beni & Pietarinen (2021a, b) for some initial studies along these directions, incorporating what Peirce takes to be characteristics of deductive reasoning, namely model-based and diagrammatic reasoning, as a central element of organism’s process of building representations of their generative models.

  3. This is also in the (implicitly) Peircean spirit of Jaynes (1995/2003: xii) who writes: “[N]either the Bayesian nor the frequentist approach is universally applicable, so in the present more general work we take a broader view of things. Our theme is simply: Probability Theory as Extended Logic. The “new” perception amounts to the recognition that the mathematical rules of probability theory are not merely rules for calculating frequencies of “random variables”; they are also the unique consistent rules for conducting inference (i.e. plausible reasoning) of any kind”. Jaynes could almost have inserted the term “abduction” within the parentheses.

  4. This technical meaning of expectations is different from its common meaning, which Peirce bundled with notions such as desires, wishes and intentions. The latter are not general otherwise than through connection with a concept. These notions do not give”ultimate intellectual interpretants” (R 318; EP 2: 430, 1907) and thus not the meaning of signs, as the meaning that they have has to be effected by reference to concepts. Expectations in futuro, in turn, appear in “mental forms” (CP 2.86) as intentions do, but do not concern conceptual meaning but the “mental effects of the signs that they interpret” (R 318; EP 2: 431). Such expectations are given in conditional forms (subjunctives), while singular expectations as such are merely non-conditional judgments.

  5. These dimensions are sketched somewhat further in Beni & Pietarinen (2021a).

  6. Among other places, this is evident in Rescher’s interpretation of Peirce’s take on science, according to which, “Science is autonomous. Corrections to science must come from science... The mistaken results of science can be improved or corrected only by further results of science. There can be no recourse at this point to tealeaf reading, numerology, the Delphic oracle or the like” (Rescher, 1978, p. 160).

  7. Such favouritism may explain some of the nearly automatic attunement of the human mind to the cognitive biases of confirmation, optimism, and the like; a topic addressed in another paper (Bobrova and Pietarinen, 2020).

References

  • Bellucci, F., & Pietarinen, A.-V. (2016). The iconic moment: Towards a theory of diagrammatic imagination. In J. Redmond (Ed.), Epistemology, knowledge and the impact of interaction (pp. 463–481). Springer.

    Google Scholar 

  • Bellucci, F., Pietarinen, A.-V. (2020a). Peirce on the justification of abduction. Studies in History and Philosophy of Science A, 84, 12–19. https://doi.org/10.1016/j.shpsa.2020.04.003

  • Bellucci, F., & Pietarinen, A.-V. (2020b). Icons, interrogations, and graphs: On Peirce's integrated notion of abduction. Transactions of the Charles S. Peirce Society, 56(1), 43–61.

  • Beni, M. D. (2018a). The reward of unification: A realist reading of the predictive processing theory. New Ideas in Psychology, 48, 21–26. https://doi.org/10.1016/j.newideapsych.2017.10.001

  • Beni, M. D. (2018b). Syntactical informational structural realism. Minds and Machines, 28(4), 623–643. https://doi.org/10.1007/s11023-018-9463-8

    Article  Google Scholar 

  • Beni, M. D. (2019a). Cognitive structural realism: A radical solution to the problem of scientific representation. Springer.

  • Beni, M. D. (2019). Conjuring cognitive structures: Towards a unified model of cognition. In A. Nepomuceno-Fernández, L. Magnani, F. Salguero-Lamillar, C. Barés-Gómez, & M. Fontaine (Eds.), Model-based reasoning in science and technology. MBR 2018 (pp. 153–172). Springer. https://doi.org/10.1007/978-3-030-32722-4_10

    Chapter  Google Scholar 

  • Pietarinen, A.-V., & Beni, M. D. (2021a). Active inference and abduction. Biosemiotics, 1–19. https://doi.org/10.1007/s12304-021-09432-0

  • Pietarinen, A.-V & Beni, M. D. (2021b). Reinvigorating a 19th-century conception of the scientific method: A Peirce-pective on science. Submitted.

  • Bobrova, A. & Pietarinen, A.-V. (2020). Two implications and dual-process theories of reasoning. In Pietarinen A.-V., et al. (Eds.), Diagrammatic representation and inference. Lecture notes in computer science 12169. Springer. https://doi.org/10.1007/978-3-030-54249-8_19

  • Champagne, M., & Pietarinen, A.-V. (2018). Why images cannot be arguments, but moving ones might. Argumentation, 34, 207–236. https://doi.org/10.1007/s10503-019-09484-0

    Article  Google Scholar 

  • Chen, A. G., Benrimoh, D., Parr, T., & Friston, K. J. (2019). A Bayesian account of generalist and specialist formation under the active inference framework. BioRxiv, 644807. https://doi.org/10.1101/644807.

  • Chiffi, D., & Pietarinen, A.-V. (2018). Abductive inference within a pragmatic framework. Synthese, 197, 2507–2523. https://doi.org/10.1007/s11229-018-1824-6

  • Chiffi, D., & Pietarinen, A.-V. (2019a). Risk and values in science: A Peircean view. Axiomathes, 29(4), 329–346. https://doi.org/10.1007/s10516-019-09419-0

    Article  Google Scholar 

  • Chiffi, D., & Pietarinen, A.-V. (2019b). The extended gabbay-woods schema and sientific practices. Natural Arguments: A Tribute to John Woods on the Occasion of his 80th Birthday (pp. 331–348). College Publications.

    Google Scholar 

  • Chiffi, D., Pietarinen, A.-V., & Proover, M. (2020). Anticipation, abduction and the economy of research: The normative stance. Futures, 115, 102471. https://doi.org/10.1016/j.futures.2019.102471

  • Colombo, M., & Hartmann, S. (2015). Bayesian cognitive science, unification, and explanation. The British Journal for the Philosophy of Science, 68(2), axv036. https://doi.org/10.1093/bjps/axv036

    Article  Google Scholar 

  • Colombo, M., & Wright, C. (2016). Explanatory pluralism: An unrewarding prediction error for free energy theorists. Brain and Cognition. https://doi.org/10.1016/j.bandc.2016.02.003

  • Cristalli, C., & Pietarinen, A.-V. (2020). Abstraction and generalization in Peirce’s logic of experimental science: Cases from the 19th-century scientific practice. HOPOS: History of Philosophy of Science, 11(1), 93–121. https://doi.org/10.1086/713087

  • Daw, N. D., Niv, Y., & Dayan, P. (2005). Uncertainty-based competition between prefrontal and dorsolateral striatal systems for behavioral control. Nature Neuroscience, 8(12), 1704–1711. https://doi.org/10.1038/nn1560

  • Dayan, P., Hinton, G. E., Neal, R. M., & Zemel, R. S. (1995). The Helmholtz machine. Neural Computation, 7(5), 889–904.

    Article  Google Scholar 

  • Friston, K. J. (2009). The free-energy principle: A rough guide to the brain? Trends in Cognitive Sciences, 13(7), 293–301. https://doi.org/10.1016/j.tics.2009.04.005

  • Friston, K. J. (2010). The free-energy principle: A unified brain theory? Nature Reviews. Neuroscience, 11(2), 127–138. https://doi.org/10.1038/nrn2787

  • Friston, K. J. (2012a). The history of the future of the Bayesian brain. NeuroImage, 62(2), 1230–1233. https://doi.org/10.1016/j.neuroimage.2011.10.004

  • Friston, K. J. (2012b). A free energy principle for biological systems. Entropy (Basel, Switzerland), 14(11), 2100–2121. https://doi.org/10.3390/e14112100

    Article  Google Scholar 

  • Friston, K. J. (2013). Active inference and free energy. Behavioral and Brain Sciences, 36(03), 212–213. https://doi.org/10.1017/S0140525X12002142

  • Friston, K. J. (2018). Am I self-conscious? Frontiers in Psychology, 9, 579. https://doi.org/10.3389/FPSYG.2018.00579

  • Friston, K. J., & Frith, C. (2015). A duet for one. Consciousness and Cognition, 36, 390–405. https://doi.org/10.1016/J.CONCOG.2014.12.003

  • Friston, K. J., Rigoli, F., Ognibene, D., Mathys, C., Fitzgerald, T., & Pezzulo, G. (2015). Active inference and epistemic value. Cognitive Neuroscience, 6(4), 187–214. https://doi.org/10.1080/17588928.2015.1020053

  • Friston, K. J., Schwartenbeck, P., FitzGerald, T., Moutoussis, M., Behrens, T., & Dolan, R. J. (2013). The anatomy of choice: Active inference and agency. Frontiers in Human Neuroscience, SEP. https://doi.org/10.3389/fnhum.2013.00598

  • Friston, K. J., & Stephan, K. E. (2007). Free-energy and the brain. Synthese, 159(3), 417–458. https://doi.org/10.1007/s11229-007-9237-y

  • Gabbay, D. M., & Woods, J. (2005). The reach of abduction. Insight and trial. Elsevier.

    Google Scholar 

  • Gabbay, D. M., & Woods, J. (2006). Advice on abductive logic. Logic Journal of the IGPL, 14(2), 189–219.

    Article  Google Scholar 

  • Gaultier, B. (2017). The iconicity of thought and its moving pictures: Following the sinuosities of Peirce’s path. Transactions of the Charles S. Peirce Society, 53(3), 374–399.

    Article  Google Scholar 

  • Giere, R. N. (1987). The cognitive study of science. In N. Nersessian (Ed.), The process of science: Contemporary philosophical approaches to understanding scientific practice (pp. 139–159). Kluwer Academic Publishers.

  • Giere, R. N. (2010). An agent-based conception of models and scientific representation. Synthese, 172(2), 269–281. https://doi.org/10.1007/s11229-009-9506-z

  • Hintikka, J. (2007). Socratic epistemology: Knowledge: Explorations of knowledge-seeking through questioning. Cambridge University Press.

    Book  Google Scholar 

  • Hohwy, J. (2014). The self-evidencing brain. Noûs, 50(2), 259–285. https://doi.org/10.1111/nous.12062

    Article  Google Scholar 

  • Jaynes, E. T. (2003/1995). Probability theory: The logic of science. Cambridge University Press.

  • Knill, D. C., & Pouget, A. (2004). The Bayesian brain: The role of uncertainty in neural coding and computation. TRENDS in Neurosciences, 27(12), 712–719. https://doi.org/10.1016/j.tins.2004.10.007

  • Ladyman, J., & Ross, D. (2007). Every thing must go. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199276196.001.0001

    Book  Google Scholar 

  • Magnani, L. (2009). Abductive cognition: The epistemological and eco-cognitive dimensions of hypothetical reasoning. Springer.

    Book  Google Scholar 

  • Magnani, L. (2017). The abductive structure of scientific creativity. Springer.

    Book  Google Scholar 

  • Ma, M., & Pietarinen, A.-V. (2018). Let us investigate! Dynamic conjecture-making as the formal logic of abduction. Journal of Philosophical Logic, 47(6), 913–945. https://doi.org/10.1007/s10992-017-9454-x

    Article  Google Scholar 

  • Maynard-Smith, J., & Price, G. R. (1973). The logic of animal conflict. Nature, 246(5427), 15–18.

    Article  Google Scholar 

  • Mayo, D. G. (2005). Peircean induction and the error-correcting thesis. Transactions of the Charles S Peirce Society, 41(2). https://doi.org/10.1353/csp.2011.0039

  • Park, W. (2017). Abduction in context: The conjectural dynamics of scientific reasoning. Springer.

    Book  Google Scholar 

  • Peirce, C. S. (1876). Note on the theory of the economy of research (R 1093). Report of the U. S. Coast Survey for 1876, pp. 197–201. Reprinted in CP 7.76–83.

  • Peirce, C. S. (1905). Letter draft to Lady Victoria Welby, July 16, 1905 (R L 493). The Peirce Papers, Harvard Houghton Library.

  • Peirce, C. S. (1913). An essay toward improving our reasoning in security and in uberty (R 682–4). The Peirce Papers, Harvard Houghton Library.

  • Peirce, C. S. (1931–1966). The collected papers of Charles S. Peirce. 8 vols., ed. by Hartshorne, C., Weiss, P., & Burks, A. W. Cambridge: Harvard University Press. Cited as CP followed by volume and paragraph number.

  • Peirce, C. S. (1967). Manuscripts in the Houghton Library of Harvard University, as identified by Richard Robin, Annotated Catalogue of the Papers of Charles S. Peirce, Amherst: University of Massachusetts Press, 1967, and in The Peirce Papers: A supplementary catalogue, Transactions of the C. S. Peirce Society 7 (1971), 37–57. Cited as R or R L (letters) followed by manuscript number and, when available, page number.

  • Peirce, C. S. (1998). The essential Peirce. Volume 2: 1893–1913. Edited by The Peirce Edition Project. Indiana University Press. Cited as EP 2.

  • Pietarinen, A.-V. (2006). Signs of logic: Peircean themes on language, games, and communication. Springer.

  • Pietarinen, A.-V. (2014). The science to save us from philosophy of science. Axiomathes, 25, 149–166.

    Article  Google Scholar 

  • Pietarinen, A.-V., & Bellucci, F. (2014). New light on Peirce's conceptions of retroduction, deduction, and scientific reasoning. International Studies in the Philosophy of Science, 28(4), 353–373.

  • Pietarinen, A.-V. (2015). Recent studies on signs: Commentary and perspectives. Sign Systems Studies, 43(4), 616–650.

    Article  Google Scholar 

  • Pietarinen, A.-V. (2018). Conjectures and abductive reasoning in games. Journal of Applied Logics - IfCoLog Journal of Logics and Its Applications, 5(5), 1121–1144.

  • Pietarinen, A.-V. (2020). Abduction and diagrams. Logic Journal of the IGPL, 29(4), 447–468. https://doi.org/10.1093/jigpal/jzz034

  • Ramstead, M. J., Kirchhoff, M. D., & Friston, K. J. (2019). A tale of two densities: Active inference is enactive inference. Adaptive Behavior, 105971231986277. https://doi.org/10.1177/1059712319862774

  • Rao, R. P., & Ballard, D. H. (1999). Predictive coding in the visual cortex: A functional interpretation of some extra-classical receptive-field effects. Nature Neuroscience, 2(1), 79–87. https://doi.org/10.1038/4580

  • Rescher, N. (1976). Peirce and the economy of research. Philosophy of Science, 43(1), 71–98. https://doi.org/10.1086/288670

    Article  Google Scholar 

  • Rescher, N. (1978). Peirce’s philosophy of science: Critical studies in his theory of induction and scientific method. University of Notre Dame Press.

  • Seth, A. K. (2014). A predictive processing theory of sensorimotor contingencies: Explaining the puzzle of perceptual presence and its absence in synesthesia. Cognitive Neuroscience, 5(2), 97–118. https://doi.org/10.1080/17588928.2013.877880

  • Shanahan, M. (2005). Perception as abduction: Turning sensor data into meaningful representation. Cognitive Science, 29(1), 103–134. https://doi.org/10.1207/s15516709cog2901_5

  • Weisberg, M. (2007). Who is a modeler? The British Journal for the Philosophy of Science, 58(2), 207–233. https://doi.org/10.1093/bjps/axm011

    Article  Google Scholar 

  • Wible, J. R. (1994). Charles Sanders Peirce’s economy of research. Journal of Economic Methodology, 1(1), 135–160. https://doi.org/10.1080/13501789400000009

  • Wible, J. R. (2019). C. S. Peirce’s theory of abductive expectations. European Journal of the History of Economic Thought, 27(1), 2–44. https://doi.org/10.1080/09672567.2019.1635179

Download references

Acknowledgements

We thank Karl J. Friston for his constructive comments on an earlier version of this paper.

Author information

Authors and Affiliations

  1. Middle East Technical University, Ankara, Turkey

    Majid D. Beni

  2. Tallinn University of Technology, Tallinn, Estonia

    Ahti-Veikko Pietarinen

  3. Research University Higher School of Economics, Moscow, Russia

    Ahti-Veikko Pietarinen

Authors
  1. Majid D. Beni
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ahti-Veikko Pietarinen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ahti-Veikko Pietarinen.

Ethics declarations

Ethical approval

No experimental human subjects involved.

Informed consent

No experimental human subjects involved.

Conflict of Interest

The authors declare no conflict of interest.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Beni, M., Pietarinen, AV. Aligning the free-energy principle with Peirce’s logic of science and economy of research. Euro Jnl Phil Sci 11, 94 (2021). https://doi.org/10.1007/s13194-021-00408-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s13194-021-00408-y

Keywords

Search

Navigation