Podsumowanie projektu „Kognitywistyka w poszukiwaniu jedności”

Projekt „Kognitywistyka w poszukiwaniu jedności” był interdyscyplinarnym przedsięwzięciem badawczym, którego celem było opracowanie ujęcia unifikacji i integracji w dziedzinie kognitywistyki. Kognitywistyka wykorzystuje narzędzia, metody i koncepcje z różnych dziedzin, co stawia pod znakiem zapytania kwestię unifikacji badań w tej dziedzinie. Projekt zespół stawiał hipotezę, że dzięki różnorodności badania interdyscyplinarne mogą zostać zunifikowane lub zintegrowane.

W projekcie analizowano modele i ramy pojęciowe stosowane w kognitywistyce, w tym teorie ucieleśnionego poznania i przetwarzania predykcyjnego. Jednakże, mimo że były one uważane za teorie unifikacyjne, okazało się, że są one tylko pewnymi wskazówkami do opracowywania zunifikowanych teorii. Projekt skupił się również na historii nauk kognitywnych i analizie pojęciowej.

Zespół projektu składał się z filozofów, psychologów poznawczych i klinicznych, którzy podejmowali badania eksperymentalne. Projekt opierał się na stanowisku neomechanicyzmu, które jest obecnie dominującym stanowiskiem we współczesnej filozofii nauki.

Dzięki projektowi udało się opracować adekwatne opisy integracji i unifikacji, co pozwoliło lepiej uzasadnić normatywne zasady udanej interdyscyplinarnej współpracy naukowej.

Raport merytoryczny z wykonania projektu udostępniamy na naszej stronie. Zawiera on listę najważniejszych publikacji wraz ze wskazaniem poszczególnych wątków naszych badań. Kompletna lista publikacji wraz z odnośnikami dostępna jest na stronie projektu tutaj – ukazało się kilka już po napisaniu raportu, może ukażą się jeszcze dwie.

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Source: Cognitive Science in Search of Unity

Models of Environment

Type Book Section
Editor Roger Frantz
Editor Leslie Marsh
Author Marcin Miłkowski
URL http://link.springer.com/10.1057/9781137442505_13
Place London
Publisher Palgrave Macmillan UK
Pages 227-238
ISBN 978-1-349-56680-8 978-1-137-44250-5
Date 2016
Extra DOI: 10.1057/9781137442505_13
Accessed 2022-12-22 17:09:26
Library Catalog DOI.org (Crossref)
Language en
Book Title Minds, Models and Milieux

Source: Publications

Testable or bust: theoretical lessons for predictive processing

Type Journal Article
Author Marcin Miłkowski
Author Piotr Litwin
URL https://link.springer.com/10.1007/s11229-022-03891-9
Volume 200
Issue 6
Pages 462
Publication Synthese
ISSN 1573-0964
Date 2022-11-02
Journal Abbr Synthese
DOI 10.1007/s11229-022-03891-9
Accessed 2022-11-04 12:05:41
Library Catalog DOI.org (Crossref)
Language en
Abstract Abstract

The predictive processing (PP) account of action, cognition, and perception is one of the most influential approaches to unifying research in cognitive science. However, its promises of grand unification will remain unfulfilled unless the account becomes theoretically robust. In this paper, we focus on empirical commitments of PP, since they are necessary both for its theoretical status to be established and for explanations of individual phenomena to be falsifiable. First, we argue that PP is a varied research tradition, which may employ various kinds of scientific representations (from theories to frameworks and toolboxes), differing in the scope of empirical commitments they entail. Two major perspectives on PP
cognitive theory may then be distinguished: generalized vs. hierarchical. The first one fails to provide empirical detail, and the latter constrains possible physical implementations. However, we show that even hierarchical PP is insufficiently restrictive to disallow incorrect models and may be adjusted to explain any neurocognitive phenomenon–including non-existent or impossible ones–through flexible adjustments. This renders PP a universal modeling tool with an unrestricted number of degrees of freedom. Therefore, in contrast with declarations of its proponents, it should not be understood as a unifying theoretical perspective, but as a computational framework, possibly informing further theory development in cognitive science.

Short Title Testable or bust

Source: Publications

Misidentification delusions as mentalization disorders

Type Journal Article
Author Adrianna Smurzyńska
URL https://doi.org/10.1007/s11097-022-09820-y
Publication Phenomenology and the Cognitive Sciences
ISSN 1572-8676
Date 2022-05-25
Journal Abbr Phenom Cogn Sci
DOI 10.1007/s11097-022-09820-y
Accessed 2022-05-26 07:58:37
Library Catalog Springer Link
Language en
Abstract The aim of this article is to analyze those theories that interpret misidentification delusions in terms of mentalization. The hypothesis under examination holds that a mentalization framework is useful for describing misidentification delusions when identification is thought to be partially based on mentalization. The article provides both a characterization and possible interpretations of such delusions, and possible relations between misidentification and mentalization are scrutinized. Whether the mentalization approach may explain or describe such kinds of mental disorders is considered, with the conclusion that while this approach is unsatisfactory, there is some room for future improvement.

Source: Publications

Piotr Kozak – Thinking with Images

The next meeting of the seminar Philosophy of Cognitive Science is planned for May, 12th, at 10:30 (AM Warsaw, CET). Our guest will be Piotr Kozak(IPS PAS). We will discuss a draft of the Introduction and Chapter 1 from his forthcoming book: Thinking with Images: Imagistic Cognition and Non-propositional Content. For the more interested we also attach Chapter 6.

From Introduction:
 The main research question of this book is: What is thinking with images? The question is analogical in its form to such questions as ‘what is thinking with language?’ It means that if we can ask whether we can think in or with language, then we can ask whether we can think in or with images.

The question follows from a commonsensical observation: when someone is asked how many windows are in his or her flat, he or she will probably form and inspect a mental image of the flat and count the windows. If an architect designs a house, then he or she designs the house with the help of drawings. If one tries to get from point to point B, one may use a map.

The examples above are instantiations of what can be called ‘thinking with images’. However, listing examples of imagistic thinking is a relatively easy task. The difficult task is to say exactly what thinking with images is.

Imagistic thinking is understood here in three ways: as a faculty, an act, and a mental state or an event. The faculty of imagistic thinking refers to the capacity of using images in thinking. The act of imagistic thinking is exercising this faculty. The mental state called ‘imagistic thought’ is a product of such an act.

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Source: Cognitive Science in Search of Unity

Without more theory, psychology will be a headless rider

Type Journal Article
Author Witold M. Hensel
Author Marcin Miłkowski
Author Przemysław Nowakowski
URL https://www.cambridge.org/core/product/identifier/S0140525X21000212/type/journal_article
Volume 45
Pages e20
Publication Behavioral and Brain Sciences
ISSN 0140-525X, 1469-1825
Date 2022
Journal Abbr Behav Brain Sci
DOI 10.1017/S0140525X21000212
Accessed 2022-02-10 08:48:42
Library Catalog DOI.org (Crossref)
Language en
Abstract Abstract
We argue that Yarkoni's proposed solutions to the generalizability crisis are half-measures because he does not recognize that the crisis arises from investigators' underappreciation of the roles of theory in experimental research. Rather than embracing qualitative analysis, the research community should make an effort to develop better theories and work toward consistently incorporating theoretical results into experimental practice.

Source: Publications

Turing’s conceptual engineering

The next meeting of the seminar is planned for February, 17th, at 10:30 (AM Warsaw, CET). Our guest will be Marcin Miłkowski (IPS PAS). We will discuss a draft paper: Turing’s conceptual engineering.

Abstract: Alan Turing’s influence on subsequent research in artificial intelligence is undeniable. His proposed test for intelligence remains influential. In this paper, Turing’s conception of how to understand intelligence is analyzed as an instance of conceptual engineering that rejects the role of the previous linguistic usage but appeals to intuition pumps instead. Even though many conceive of his proposal as a prime case of operationalism or behaviorism, it is more plausibly viewed as a stepping stone toward a future theoretical construal of intelligence. In addition, his own conceptual network is analyzed through the lens of distributional semantics over the corpus of his written work. As it turns out, Turing’s conceptual engineering of the notion of “intelligence” is indeed quite similar to providing a precising definition with the aim of revising the usage of the concept.

Get a Google Meet link by emailing pnowakowski@ifispan.edu.pl

Turing’s conceptual engineering

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Source: Cognitive Science in Search of Unity

Incorporating free energy models into mechanisms: the case of predictive processing under the free energy principle

The next meeting of the seminar is planned for January, 20th, at 11:00 (AM Warsaw, CET). Our guest will be Michał Piekarski (UKSW Warsaw). We will discuss a draft paper: Incorporating free energy models into mechanisms: the case of predictive processing under the free energy principle.

Abstract: There is a view emerging in the philosophy of science that research practices in science can be characterized in terms of discovering and describing mechanisms. Mechanistic explanations are based on the identifying the underlying mechanisms that generate a target phenomenon and strategies understood as decomposition of these mechanisms. Recently, there has been a discussion among mechanists about the necessity to include constraints and free energy flows into the explanations, as constitutive components of mechanistic explanations. This is directly related to the existence of control mechanisms that are non-autonomous and entail the existence of heterarchical networks. I refer to this as the ‘constrained mechanisms approach’. This paper examines the extent to which this approach can be applied to the predictive processing framework, which is now an influential process theory, offering a computational description of perceptual and cognitive mechanisms in terms of hierarchical generative models approximating Bayesian inference. In other words, I examine whether the constrained mechanisms approach can be applied to the framework in which control mechanisms play an important explanatory role. I will argue that predictive processing models based on the free energy principle are amenable to this approach. In practice, this means that free energy principle offers a normative explanatory framework for predictive processing, and that in turn, this framework offers a biologically plausible account of the manner in which the principle is implemented in terms of hierarchical generative models and heterarchical active mechanisms. These analyzes are of great importance for those approaches that undermine the explanatory status of the free energy principle.


Zgłoszenia należy wysłać na mail: pnowakowski@ifispan.waw.pl

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Source: Cognitive Science in Search of Unity

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