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Marcin Miłkowski
Polish Academy of Sciences
  1.  80
    Explaining the Computational Mind.Marcin Miłkowski - 2013 - MIT Press.
    In the book, I argue that the mind can be explained computationally because it is itself computational—whether it engages in mental arithmetic, parses natural language, or processes the auditory signals that allow us to experience music. All these capacities arise from complex information-processing operations of the mind. By analyzing the state of the art in cognitive science, I develop an account of computational explanation used to explain the capacities in question.
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  2.  83
    Structural Representations: Causally Relevant and Different From Detectors.Paweł Gładziejewski & Marcin Miłkowski - 2017 - Biology and Philosophy 32 (3):337-355.
    This paper centers around the notion that internal, mental representations are grounded in structural similarity, i.e., that they are so-called S-representations. We show how S-representations may be causally relevant and argue that they are distinct from mere detectors. First, using the neomechanist theory of explanation and the interventionist account of causal relevance, we provide a precise interpretation of the claim that in S-representations, structural similarity serves as a “fuel of success”, i.e., a relation that is exploitable for the representation using (...)
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  3. Explanatory Completeness and Idealization in Large Brain Simulations: A Mechanistic Perspective.Marcin Miłkowski - 2016 - Synthese 193 (5):1457-1478.
    The claim defended in the paper is that the mechanistic account of explanation can easily embrace idealization in big-scale brain simulations, and that only causally relevant detail should be present in explanatory models. The claim is illustrated with two methodologically different models: Blue Brain, used for particular simulations of the cortical column in hybrid models, and Eliasmith’s SPAUN model that is both biologically realistic and able to explain eight different tasks. By drawing on the mechanistic theory of computational explanation, I (...)
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  4. The Hard Problem Of Content: Solved (Long Ago).Marcin Miłkowski - 2015 - Studies in Logic, Grammar and Rhetoric 41 (1):73-88.
    In this paper, I argue that even if the Hard Problem of Content, as identified by Hutto and Myin, is important, it was already solved in natu- ralized semantics, and satisfactory solutions to the problem do not rely merely on the notion of information as covariance. I point out that Hutto and Myin have double standards for linguistic and mental representation, which leads to a peculiar inconsistency. Were they to apply the same standards to basic and linguistic minds, they would (...)
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  5. From Wide Cognition to Mechanisms: A Silent Revolution.Marcin Miłkowski, Robert Clowes, Zuzanna Rucińska, Aleksandra Przegalińska, Tadeusz Zawidzki, Joel Krueger, Adam Gies, Marek McGann, Łukasz Afeltowicz, Witold Wachowski, Fredrik Stjernberg, Victor Loughlin & Mateusz Hohol - 2018 - Frontiers in Psychology 9.
    In this paper, we argue that several recent ‘wide’ perspectives on cognition (embodied, embedded, extended, enactive, and distributed) are only partially relevant to the study of cognition. While these wide accounts override traditional methodological individualism, the study of cognition has already progressed beyond these proposed perspectives towards building integrated explanations of the mechanisms involved, including not only internal submechanisms but also interactions with others, groups, cognitive artifacts, and their environment. The claim is substantiated with reference to recent developments in the (...)
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  6. From Computer Metaphor to Computational Modeling: The Evolution of Computationalism.Marcin Miłkowski - 2018 - Minds and Machines 28 (3):515-541.
    In this paper, I argue that computationalism is a progressive research tradition. Its metaphysical assumptions are that nervous systems are computational, and that information processing is necessary for cognition to occur. First, the primary reasons why information processing should explain cognition are reviewed. Then I argue that early formulations of these reasons are outdated. However, by relying on the mechanistic account of physical computation, they can be recast in a compelling way. Next, I contrast two computational models of working memory (...)
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  7.  33
    Unification by Fiat: Arrested Development of Predictive Processing.Piotr Litwin & Marcin Miłkowski - 2020 - Cognitive Science 44 (7).
    Predictive processing (PP) has been repeatedly presented as a unificatory account of perception, action, and cognition. In this paper, we argue that this is premature: As a unifying theory, PP fails to deliver general, simple, homogeneous, and systematic explanations. By examining its current trajectory of development, we conclude that PP remains only loosely connected both to its computational framework and to its hypothetical biological underpinnings, which makes its fundamentals unclear. Instead of offering explanations that refer to the same set of (...)
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  8. Satisfaction Conditions in Anticipatory Mechanisms.Marcin Miłkowski - 2015 - Biology and Philosophy 30 (5):709-728.
    The purpose of this paper is to present a general mechanistic framework for analyzing causal representational claims, and offer a way to distinguish genuinely representational explanations from those that invoke representations for honorific purposes. It is usually agreed that rats are capable of navigation because they maintain a cognitive map of their environment. Exactly how and why their neural states give rise to mental representations is a matter of an ongoing debate. I will show that anticipatory mechanisms involved in rats’ (...)
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  9. Unification Strategies in Cognitive Science.Marcin Miłkowski - 2016 - Studies in Logic, Grammar and Rhetoric 48 (1):13–33.
    Cognitive science is an interdisciplinary conglomerate of various research fields and disciplines, which increases the risk of fragmentation of cognitive theories. However, while most previous work has focused on theoretical integration, some kinds of integration may turn out to be monstrous, or result in superficially lumped and unrelated bodies of knowledge. In this paper, I distinguish theoretical integration from theoretical unification, and propose some analyses of theoretical unification dimensions. Moreover, two research strategies that are supposed to lead to unification are (...)
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  10. The False Dichotomy Between Causal Realization and Semantic Computation.Marcin Miłkowski - 2017 - Hybris. Internetowy Magazyn Filozoficzny 38:1-21.
    In this paper, I show how semantic factors constrain the understanding of the computational phenomena to be explained so that they help build better mechanistic models. In particular, understanding what cognitive systems may refer to is important in building better models of cognitive processes. For that purpose, a recent study of some phenomena in rats that are capable of ‘entertaining’ future paths (Pfeiffer and Foster 2013) is analyzed. The case shows that the mechanistic account of physical computation may be complemented (...)
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  11. Beyond Formal Structure: A Mechanistic Perspective on Computation and Implementation.Marcin Miłkowski - 2011 - Journal of Cognitive Science 12 (4):359-379.
    In this article, after presenting the basic idea of causal accounts of implementation and the problems they are supposed to solve, I sketch the model of computation preferred by Chalmers and argue that it is too limited to do full justice to computational theories in cognitive science. I also argue that it does not suffice to replace Chalmers’ favorite model with a better abstract model of computation; it is necessary to acknowledge the causal structure of physical computers that is not (...)
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  12.  39
    Function and Causal Relevance of Content.Marcin Miłkowski - 2016 - New Ideas in Psychology 40 (94-102).
    In this paper, I focus on a problem related to teleological theories of content namely, which notion of function makes content causally relevant? It has been claimed that some functional accounts of content make it causally irrelevant, or epiphenomenal; in which case, such notions of function could no longer act as the pillar of naturalized semantics. By looking closer at biological questions about behavior, I argue that past discussion has been oriented towards an ill-posed question. What I defend is a (...)
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  13. Objections to Computationalism: A Survey.Marcin Miłkowski - 2018 - Roczniki Filozoficzne 66 (3):57-75.
    In this paper, the Author reviewed the typical objections against the claim that brains are computers, or, to be more precise, information-processing mechanisms. By showing that practically all the popular objections are based on uncharitable interpretations of the claim, he argues that the claim is likely to be true, relevant to contemporary cognitive science, and non-trivial.
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  14. Representational Unification in Cognitive Science: Is Embodied Cognition a Unifying Perspective?Marcin Miłkowski & Przemysław Nowakowski - forthcoming - Synthese.
    In this paper, we defend a novel, multidimensional account of representational unification, which we distinguish from integration. The dimensions of unity are simplicity, generality and scope, non-monstrosity, and systematization. In our account, unification is a graded property. The account is used to investigate the issue of how research traditions contribute to representational unification, focusing on embodied cognition in cognitive science. Embodied cognition contributes to unification even if it fails to offer a grand unification of cognitive science. The study of this (...)
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  15. Integrating Cognitive (Neuro)Science Using Mechanisms.Marcin Miłkowski - 2016 - Avant: Trends in Interdisciplinary Studies (2):45-67.
    In this paper, an account of theoretical integration in cognitive (neuro)science from the mechanistic perspective is defended. It is argued that mechanistic patterns of integration can be better understood in terms of constraints on representations of mechanisms, not just on the space of possible mechanisms, as previous accounts of integration had it. This way, integration can be analyzed in more detail with the help of constraintsatisfaction account of coherence between scientific representations. In particular, the account has resources to talk of (...)
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  16. Why Think That the Brain is Not a Computer?Marcin Miłkowski - 2016 - APA Newsletter on Philosophy and Computers 16 (2):22-28.
    In this paper, I review the objections against the claim that brains are computers, or, to be precise, information-processing mechanisms. By showing that practically all the popular objections are either based on uncharitable interpretation of the claim, or simply wrong, I argue that the claim is likely to be true, relevant to contemporary cognitive (neuro)science, and non-trivial.
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  17. Situatedness and Embodiment of Computational Systems.Marcin Miłkowski - 2017 - Entropy 19 (4):162.
    In this paper, the role of the environment and physical embodiment of computational systems for explanatory purposes will be analyzed. In particular, the focus will be on cognitive computational systems, understood in terms of mechanisms that manipulate semantic information. It will be argued that the role of the environment has long been appreciated, in particular in the work of Herbert A. Simon, which has inspired the mechanistic view on explanation. From Simon’s perspective, the embodied view on cognition seems natural but (...)
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  18. Replicability or Reproducibility? On the Replication Crisis in Computational Neuroscience and Sharing Only Relevant Detail.Marcin Miłkowski, Witold M. Hensel & Mateusz Hohol - 2018 - Journal of Computational Neuroscience 3 (45):163-172.
    Replicability and reproducibility of computational models has been somewhat understudied by “the replication movement.” In this paper, we draw on methodological studies into the replicability of psychological experiments and on the mechanistic account of explanation to analyze the functions of model replications and model reproductions in computational neuroscience. We contend that model replicability, or independent researchers' ability to obtain the same output using original code and data, and model reproducibility, or independent researchers' ability to recreate a model without original code, (...)
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  19.  12
    Prospection Does Not Imply Predictive Processing.Piotr Litwin & Marcin Miłkowski - 2020 - Behavioral and Brain Sciences 43.
    Predictive processing models of psychopathologies are not explanatorily consistent with the present account of abstract thought. These models are based on latent variables probabilistically mapping the structure of the world. As such, they cannot be informed by representational ontology based on mental objects and states. What actually is the case is merely some terminological affinity between subjective and informational uncertainty.
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  20. Computational Mechanisms and Models of Computation.Marcin Miłkowski - 2014 - Philosophia Scientiae 18:215-228.
    In most accounts of realization of computational processes by physical mechanisms, it is presupposed that there is one-to-one correspondence between the causally active states of the physical process and the states of the computation. Yet such proposals either stipulate that only one model of computation is implemented, or they do not reflect upon the variety of models that could be implemented physically. -/- In this paper, I claim that mechanistic accounts of computation should allow for a broad variation of models (...)
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  21.  84
    Morphological Computation: Nothing but Physical Computation.Marcin Miłkowski - 2018 - Entropy 10 (20):942.
    The purpose of this paper is to argue against the claim that morphological computation is substantially different from other kinds of physical computation. I show that some (but not all) purported cases of morphological computation do not count as specifically computational, and that those that do are solely physical computational systems. These latter cases are not, however, specific enough: all computational systems, not only morphological ones, may (and sometimes should) be studied in various ways, including their energy efficiency, cost, reliability, (...)
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  22.  10
    Cognitive Artifacts for Geometric Reasoning.Mateusz Hohol & Marcin Miłkowski - 2019 - Foundations of Science 24 (4):657-680.
    In this paper, we focus on the development of geometric cognition. We argue that to understand how geometric cognition has been constituted, one must appreciate not only individual cognitive factors, such as phylogenetically ancient and ontogenetically early core cognitive systems, but also the social history of the spread and use of cognitive artifacts. In particular, we show that the development of Greek mathematics, enshrined in Euclid’s Elements, was driven by the use of two tightly intertwined cognitive artifacts: the use of (...)
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  23.  48
    A Mechanistic Account of Computational Explanation in Cognitive Science and Computational Neuroscience.Marcin Miłkowski - 2016 - In Vincent C. Müller (ed.), Computing and Philosophy. Springer. pp. 191-205.
    Explanations in cognitive science and computational neuroscience rely predominantly on computational modeling. Although the scientific practice is systematic, and there is little doubt about the empirical value of numerous models, the methodological account of computational explanation is not up-to-date. The current chapter offers a systematic account of computational explanation in cognitive science and computational neuroscience within a mechanistic framework. The account is illustrated with a short case study of modeling of the mirror neuron system in terms of predictive coding.
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  24. Is Computationalism Trivial?Marcin Miłkowski - 2007 - In Gordana Dodig Crnkovic & Susan Stuart (eds.), Computation, Information, Cognition: The Nexus and the Liminal. Cambridge Scholars Press.
    In this paper, I want to deal with the triviality threat to computationalism. On one hand, the controversial and vague claim that cognition involves computation is still denied. On the other, contemporary physicists and philosophers alike claim that all physical processes are indeed computational or algorithmic. This claim would justify the computationalism claim by making it utterly trivial. I will show that even if these two claims were true, computationalism would not have to be trivial.
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  25.  4
    Models of Environment.Marcin Miłkowski - 2016 - In Roger Frantz & Leslie Marsh (eds.), Minds, Models and Milieux. Commemorating the Centennial of the Birth of Herbert Simon. Palgrave-Macmillan. pp. 227-238.
    Herbert A. Simon is well known for his account of bounded rationality. Whereas classical economics idealized economic agency and framed rational choice in terms of the decision theory, Simon insisted that agents need not be optimal in their choices. They might be mere satispcers, i.e., attain good enough goals rather than optimal ones. At the same time, behaviorally as well as computationally, bounded rationality is much more realistic.
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  26. Limits of Computational Explanation of Cognition.Marcin Miłkowski - 2013 - In Vincent C. Müller (ed.), Philosophy and Theory of Artificial Intelligence. Springer. pp. 69-84.
    In this chapter, I argue that some aspects of cognitive phenomena cannot be explained computationally. In the first part, I sketch a mechanistic account of computational explanation that spans multiple levels of organization of cognitive systems. In the second part, I turn my attention to what cannot be explained about cognitive systems in this way. I argue that information-processing mechanisms are indispensable in explanations of cognitive phenomena, and this vindicates the computational explanation of cognition. At the same time, it has (...)
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  27. Wyjaśnianie w kognitywistyce.Marcin Miłkowski - 2013 - Przeglad Filozoficzny - Nowa Seria 86 (2):151-166.
    The paper defends the claim that the mechanistic explanation of information processing is the fundamental kind of explanation in cognitive science. These mechanisms are complex organized systems whose functioning depends on the orchestrated interaction of their component parts and processes. A constitutive explanation of every mechanism must include both appeal to its environment and to the role it plays in it. This role has been traditionally dubbed competence. To fully explain how this role is played it is necessary to explain (...)
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  28. Reverse-Engineering in Cognitive-Science.Marcin Miłkowski - 2013 - In Marcin Miłkowski & Konrad Talmont-Kaminski (eds.), Regarding Mind, Naturally. Cambridge Scholars Press. pp. 12-29.
    I discuss whether there are some lessons for philosophical inquiry over the nature of simulation to be learnt from the practical methodology of reengineering. I will argue that reengineering serves a similar purpose as simulations in theoretical science such as computational neuroscience or neurorobotics, and that the procedures and heuristics of reengineering help to develop solutions to outstanding problems of simulation.
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  29. Computational Mechanisms and Models of Computation.Marcin Miłkowski - 2014 - Philosophia Scientae 18:215-228.
    In most accounts of realization of computational processes by physical mechanisms, it is presupposed that there is one-to-one correspondence between the causally active states of the physical process and the states of the computation. Yet such proposals either stipulate that only one model of computation is implemented, or they do not reflect upon the variety of models that could be implemented physically. In this paper, I claim that mechanistic accounts of computation should allow for a broad variation of models of (...)
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  30. Definining Ontological Naturalism.Marcin Miłkowski - 2008 - In Alexander Hieke & Hannes Leitgeb (eds.), Reduction and Elimination in Philosophy and the Sciences. Papers of the 31st International Wittgenstein Symposium. Austrian Ludwig Wittgenstein Society.
    Many philosophers use “physicalism” and “naturalism” interchangeably. In this paper, I will distinguish ontological naturalism from physicalism. While broad versions of physicalism are compatible with naturalism, naturalism doesn't have to be committed to strong versions of physical reductionism, so it cannot be defined as equivalent to it. Instead of relying on the notion of ideal physics, naturalism can refer to the notion of ideal natural science that doesn't imply unity of science. The notion of ideal natural science, as well as (...)
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  31. Czym jest i jak istnieje umysł?Marcin Miłkowski & Robert Poczobut - 2005 - Diametros 3:27-55.
    The goal of the article is to show that a complete answer to the title question can be given only in the context of the natural sciences. We believe that the group of cognitive sciences are the most reliable source of information about cognitive mental processes is. Making use of their achievements we present a series of criteria for possessing a mind. We distinguish between many kinds of minds . We attempt to outline the conditions that must be fulfilled by (...)
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  32.  53
    When Weak Modularity is Robust Enough?Marcin Miłkowski - 2008 - Análisis Filosófico 28 (1):77-89.
    In this paper, I suggest that the notion of module explicitly defined by Peter Carruthers in The Architecture of The Mind (Carruthers 2006) is not really In use in the book. Instead, a more robust notion seems to be actually in play. The more robust notion, albeit implicitly assumed, seems to be far more useful for making claims about the modularity of mind. Otherwise, the claims would become trivial. This robust notion will be reconstructed and improved upon by putting it (...)
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  33. Idyllic Heroism: Nietzsche's View of Epicurus.Marcin Miłkowski - 1998 - Journal of Nietzsche Studies 15:70-79.
    In this paper, Nietzsche's interpretation of Epicurus is sketched. The ancient philosopher is seen as subscribing to 'idyllic heroism', i.e., heroically adopting an idyllic way of life.
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  34. Mechanistic Computational Individuation Without Biting the Bullet.Nir Fresco & Marcin Miłkowski - 2019 - British Journal for the Philosophy of Science:axz005.
    Is the mathematical function being computed by a given physical system determined by the system’s dynamics? This question is at the heart of the indeterminacy of computation phenomenon (Fresco et al. [unpublished]). A paradigmatic example is a conventional electrical AND-gate that is often said to compute conjunction, but it can just as well be used to compute disjunction. Despite the pervasiveness of this phenomenon in physical computational systems, it has been discussed in the philosophical literature only indirectly, mostly with reference (...)
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  35.  4
    Mechanistic Computational Individuation Without Biting the Bullet.Nir Fresco & Marcin Miłkowski - 2021 - British Journal for the Philosophy of Science 72 (2):431-438.
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  36. Book Review: Jeff Buechner, Gödel, Putnam, and Functionalism: A New Reading of Representation and Reality. [REVIEW]Witold M. Hensel & Marcin Miłkowski - 2014 - Journal of Cognitive Science 15 (3):391-402.
  37.  26
    Regarding Mind, Naturally.Marcin Miłkowski & Konrad Talmont-Kaminski (eds.) - 2013 - Cambridge Scholars Press.
    Naturalism is currently the most vibrantly developing approach to philosophy, with naturalised methodologies being applied across all the philosophical disciplines. One of the areas naturalism has been focussing upon is the mind, traditionally viewed as a topic hard to reconcile with the naturalistic worldview. A number of questions have been pursued in this context. What is the place of the mind in the world? How should we study the mind as a natural phenomenon? What is the significance of cognitive science (...)
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  38. Analityczna Metafizyka Umysłu: Najnowsze Kontrowersje.Marcin Miłkowski & Robert Poczobut (eds.) - 2008 - Wydawn. Instytutu Filozofii I Socjologii Polskiej Akademii Nauk.
  39. Computation and Multiple Realizability.Marcin Miłkowski - 2016 - In Vincent Müller (ed.), Fundamental Issues of Artificial Intelligence. Springer. pp. 29-41.
    Multiple realizability (MR) is traditionally conceived of as the feature of computational systems, and has been used to argue for irreducibility of higher-level theories. I will show that there are several ways a computational system may be seen to display MR. These ways correspond to (at least) five ways one can conceive of the function of the physical computational system. However, they do not match common intuitions about MR. I show that MR is deeply interest-related, and for this reason, difficult (...)
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  40. Czy Nietzsche mógł mieć rację?Marcin Miłkowski - 2003 - Przegląd Filozoficzno-Literacki 1 (1):213-235.
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  41.  19
    Correspondence Theory of Semantic Information.Marcin Miłkowski - forthcoming - British Journal for the Philosophy of Science.
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  42.  88
    Co to wszystko znaczy? (recenzja To wszystko nic nie znaczy Krzysztofa Posłajki). [REVIEW]Marcin Miłkowski - 2014 - Przegląd Filozoficzno-Literacki 2:331-339.
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  43. Dlaczego Wittgenstein nie był dualistą.Marcin Miłkowski - 2002 - Przeglad Filozoficzny - Nowa Seria 44 (4):69-83.
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  44.  22
    Demokryt w oczach Nietzschego.Marcin Miłkowski - 2005 - Nowa Krytyka 15.
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  45. Evaluating Artificial Models of Cognition.Marcin Miłkowski - 2015 - Studies in Logic, Grammar and Rhetoric 40 (1):43-62.
    Artificial models of cognition serve different purposes, and their use determines the way they should be evaluated. There are also models that do not represent any particular biological agents, and there is controversy as to how they should be assessed. At the same time, modelers do evaluate such models as better or worse. There is also a widespread tendency to call for publicly available standards of replicability and benchmarking for such models. In this paper, I argue that proper evaluation ofmodels (...)
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  46.  22
    Explanations in Cognitive Science: Unification Versus Pluralism.Marcin Miłkowski & Mateusz Hohol - forthcoming - Synthese:1-17.
    The debate between the defenders of explanatory unification and explanatory pluralism has been ongoing from the beginning of cognitive science and is one of the central themes of its philosophy. Does cognitive science need a grand unifying theory? Should explanatory pluralism be embraced instead? Or maybe local integrative efforts are needed? What are the advantages of explanatory unification as compared to the benefits of explanatory pluralism? These questions, among others, are addressed in this Synthese’s special issue. In the introductory paper, (...)
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  47.  28
    Evolutionist of Intelligence. Introduction.Marcin Miłkowski - 2011 - Avant: Trends in Interdisciplinary Studies 2 (2):29-33.
    It would be hard to find a more fervent advocate of the position that computers are of profound significance to philosophy than Aaron Sloman. Yet, he is not a stereotypical proponent of Artificial Intelligence (AI). Far from it; in his writings, he undermines several popular convictions of functionalists. Through his drafts and polemics, Sloman definitely exerts quite substantial influence on the philosophy of Artificial Intelligence. Sloman's paper “Evolution: The Computer Systems Engineer Designing Minds” presents a bold hypothesis that the evolution (...)
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  48. Epistemologia Znaturalizowana.Marcin Miłkowski - 2013 - In . Wam. pp. 495-524.
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  49. Filozofia jako inżynieria odwrotna: rzecz o naturalizmie Daniela C. Dennetta.Marcin Miłkowski - 2004 - Przeglad Filozoficzny - Nowa Seria 50 (2):75-89.
  50. Heroizm idylliczny - Epikur w oczach Nietzschego.Marcin Miłkowski - 1998 - Przeglad Filozoficzny - Nowa Seria 28 (4):121-135.
    Nietzsche's treatment of Epicurus is an interesting example of philosophical hermeneutics. Epicurus bas tren notoriously misinterpreted, claims Nietzsche, because bis mask bas been taken for bis true face. Traditionally Epicurus is presented as a utilitarian or hedonist avant la lettre. This is a simplification motivated by a desire to deprecate bis philosophy. To Nietzsche Epicurus was „an idyllic hero”, a teacher with anistocratic predilections aun his own concept of good, critical of the traditional form of religion, and of the „pre-existent (...)
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