By taking into account some texts published between the first and the second edition of the Critique of Pure Reason that have been neglected by most of those who have dealt with the deduction of the categories, I argue that the core of the deduction is to be identified as the ‘almost single inference from the precisely determined definition of a judgment in general’, which Kant adumbrates in the Metaphysical Foundations in order to ‘make up for the deficiency’ of the (...) A-deduction. Whereas the first step of the B-deduction is an attempt to show that the manifold of an intuition belongs to the ‘necessary unity of self-consciousness’ by means of the synthesis of the understanding, the second step has the task of showing that the very same synthesis is responsible for the spatio-temporal unity of the manifold. Thus, Kant's ‘answer to Hume’ is that no spatio-temporal objects of experience at all are merely ‘given’, independently of the conceptual activities of the understanding. Against the established view I substantiate the claim that with this ‘almost single inference’ of the second proof step the distinction between judgments of perception and judgments of experience consequently vanished from Kant's thinking. (shrink)

Most engineering reasoning in practice is about how to achieve some predetermined end. Despite its paramount importance, this form of reasoning has hardly been investigated in the literature.a The aim of this paper is therefore to explore the question to what extent technical norms can be said to have a truth-value, and under what conditions practical inferences are deductively valid. We take technical norms to be sentences of the form ‘If you want A, and you are in a situation B, (...) then you ought to do X’. Von Wright’s standard example of making a hut habitable is our paradigm for practical inferences, where an obligation to act is deduced from an intention to realize an end, and an empirical constraint on how this end can be achieved. Our instrument of analysis is dynamic logic (PDL), since actions are aimed at changing the world. PDL already suffices to provide truth-conditions for technical norms. To accommodate the obligation in practical inferences we draw on John Jules Meyer’s deontic version of PDL. By paraphrasing ‘person P wants’ with ‘person P imposes an obligation on herself,’ we can give a plausible definition of the validity of practical inferences. In the discussion section, we address the issues of the reliability instead of truth-value of technical norms, and of the defeasibility of practical inferences as they occur in engineering practice. (shrink)

Shin and DuBrow propose that a key principle driving event segmentation relates to causal analyses: specifically, that experiences that are attributed as having the same underlying cause are grouped together into an event. This offers an alternative to accounts of segmentation based on prediction error.

Conflict resolution is a core component of healthcare ethics consultation (HEC) and proficiency in this skill set is recognized by the national bioethics organization and its HEC certification process. Difficult interpersonal interactions between the clinical team and patients or their families are often inexorably connected to the normative disputes that are the catalyst for the consult. Ethics consultants are often required to navigate challenging dynamics that have become entrenched and work with patient-provider or family-provider relationships that have already broken down. (...) The first step in conflict resolution is diagnosing the source of the conflict. Because so many interpersonal and normative conflicts rest on misunderstanding and mischaracterization, the diagnosis of the problem requires untangling the actual positions and perspectives of the conflicting parties from the fallacious assumptions made about the parties’ respective positions and views. Developed in management science, the Ladder of Inference (LOI) is a diagnostic tool for assisting stakeholders in re-examining the process they used to form beliefs about others involved in the conflict. The LOI is a device that detects errors in reasoning, including implicit racial bias, that lead to false judgments and counterproductive responses to those judgments. The LOI is an instrument that can be used by ethics consultants to help resolve contentious bedside conflicts, but the LOI can also be employed as a teaching tool used by healthcare ethics consultants in training the clinical staff in how to avoid such conflicts in the first place. (shrink)

The paper presents an analysis of the anumāna chapter of Jayarāśi’s Tattvôpaplava-siṁha and the nature of his criticism levelled against the anumāna model. The results of the analysis force us to revise our understanding of Jayarāśi Bhaṭṭa as a sceptic. Instead, he emerges as a highly critical philosopher. In addition, the nature of Jayarāśi’s criticism of the anumāna model allow us to conclude that anumāna should not be equated with inference, but rather is its limited subset, and may at best (...) be rendered as ‘disputational inference’, ‘debational inference’ or even ‘dialogical inference’. Jayarāśi applies a range of logical laws which clearly represent patterns of what can be classified as a priori reasoning and analytical justifications for knowledge, which were traditionally not reckoned sound. Against the backdrop of Jayarāśi’s criticism of anumāna, the paper also attempts to provide an explanation to why Indian philosophy and logic did not develop any concept of proper symbols and variables. (shrink)

Para entender por qué la interacción de la ciencia y el derecho puede ser tan problemática, no basta con apuntar vagamente hacia un supuesto contraste entre los “modos de pensamiento” científico y jurídico. Es necesario considerar, en cambio, las consecuencias de los distintos objetivos que tanto la ciencia como el derecho persiguen, así como las limitaciones bajo las cuales dichos objetivos son perseguidos, y las diferentes culturas que involucran a ambas empresas. Desde esa perspectiva, es posible observar no sólo por (...) qué el derecho en algunas ocasiones pide más de lo que la ciencia puede dar en tanto que en otras recibe menos de lo que la ciencia podría dar, sino también por qué la simple dicotomía “inferencia científica” vs. “razonamiento jurídico” es en realidad más engañosa que útil. (shrink)

Social epistemology presents different theories about the status of shared knowledge, but only some of them retain a fruitful relation with classical epistemology. The aim of my contribution is to present a pragmatic model which is, on the one side, related to the classical concepts of “truth” and “justification”, while, on the other side, addressing to a fundamentally “social” structure for the justification of knowledge. The shift from formal semantics to pragmatics is based on a notion of “material inference” embedding (...) commitments implicit in the use of language, that favors the recognition of the social source of shared knowledge. (shrink)

Chris Kaposy's article “The Supposed Obligation to Change One's Beliefs About Ethics Because of Discoveries in Neuroscience” (2010) targets a common “inference” among neuroscientists and ethicists....

The Paper Begins by introducing the Siren “psychogenic inference”. It then deals with the impact of this inference on the navigation of medical and psychiatric seafarers. The next two parts are more theoretical; the first deals with the entrenchment of the psychogenic inference in some central terms used in discussing medically unexplained symptoms (MUS). The second uncovers the damaging influence of the psychogenic inference on the navigational charts—on the somatoform disorder sections of the two major classifications used internationally, namely the (...) Diagnostic and Statistical Manual, 4th edition Text revision (DSM-IV-TR; American Psychiatric Association [APA] 1994), produced by the APA and of the International .. (shrink)

본 연구는 “교육학적 추론을 위한 베이지언 모델”의 형식적 타당성 및 이 모델이 갖는 교육학적 함의와 인식론적 함의에 대해 비판적으로 검토한다.BR 베이즈주의 학습이론가들에 따르면, 교육학적 목표를 가장 잘 성취하기 위해서는 “정확한 가설”(h)에 대한 학습자의 믿음을 최대화하는 “데이터”(d)를 교사가 선택해야 한다. 달리 말하면, 학생이 추측하는 문제의 가설(개념)이 교사가 목표로 하는 바로 그 가설(개념)에 최대로 가까워지게 하는 예시를 교사가 학생에게 제공해야 한다. 이를 위해서는 교사가 생산하는 “데이터의 분포”(p teacher (d｜h))가 “가설(h)에 대한 학습자의 사후 믿음”(p learner (h｜d))을 최대화하는 데이터들을 중심으로 균등하게 분포되어야 할 것이다. (...) 학생은 처음부터 문제의 개념을 소유하고 있지 않다. 학생은 교사가 제공하는 예시를 통해서 비로소 개념을 구성해야 하는 위치에 있다. 이를 위해서 우선 교사는 학생의 인지 상태를 알고 있어야 한다. 즉 학생이 어떤 데이터를 접하게 될 때, 어떤 개념을 상상할 것이라고 교사는 예측해야 한다. 결국 교사는 “p teacher (d｜h)” 와 “p learner (h｜d)”, 양자 모두를 알아야 한다. 이러한 맥락에서 교사가 활용할 수 있는 모델이 아래와 같은 방정식이다.BR 이것이 베이지언 학습이론가들이 지지하는 “교육학적 추론 모델”이다. 그들에 따르면, 이 방정식의 해는 문제의 개념(가설)을 가장 잘 전달하게 할 예시 선택을 가능하게 하는 대안이다. 그런데 이 모델이 구체적 교육 현장에서 어떻게 적용될 수 있는가를 보기 위해서, 또한 이 모델이 가지는 논리-형식적 타당성 및 교육-인식론적 함의를 이해하기 위해서, 필자는 베이지언 이론가들이 제시하는 많은 예시들 중에서 가장 단순한 예시인 “선 게임 이론”(theory of line game)을 분석하고자 한다.BR. (shrink)

“Evidence” in the form of data collected and analysis thereof is fundamental to medicine, health and science. In this paper, we discuss the “evidence-based” aspect of evidence-based medicine in terms of statistical inference, acknowledging that this latter field of statistical inference often also goes by various near-synonymous names—such as inductive inference (amongst philosophers), econometrics (amongst economists), machine learning (amongst computer scientists) and, in more recent times, data mining (in some circles). Three central issues to this discussion of “evidence-based” are (i) (...) whether or not the statistical analysis can and/or should be objective and/or whether or not (subjective) prior knowledge can and/or should be incorporated, (ii) whether or not the analysis should be invariant to the framing of the problem (e.g. does it matter whether we analyse the ratio of proportions of morbidity to non-morbidity rather than simply the proportion of morbidity?), and (iii) whether or not, as we get more and more data, our analysis should be able to converge arbitrarily closely to the process which is generating our observed data. For many problems of data analysis, it would appear that desiderata (ii) and (iii) above require us to invoke at least some form of subjective (Bayesian) prior knowledge. This sits uncomfortably with the understandable but perhaps impossible desire of many medical publications that at least all the statistical hypothesis testing has to be classical non-Bayesian—i.e. it is not permitted to use any (subjective) prior knowledge. (shrink)

In this article, I first give a short outline of the different interpretations of the concept of probability that emerged in the twentieth century. In what follows, I give an overview of the main problems and problematic concepts from the philosophy of probability and show how they relate to Bayesian inference. In this overview, I emphasise that the understanding of the main concepts related to different interpretations of probability influences the understanding and status of Bayesian inference. In the conclusion, I (...) express that, from a broad epistemological point of view, a kind of compatibilism between the two main lines of interpretations of probability is worth pursuing, as they represent different aspects of the epistemological process. (shrink)

Nyana is the most rational and logical of all the classical Indian philosophical systems. In the study of Nyana philosophy, Karikavali with its commentary Muktavali, both by Visvanatha Nyayapancanana, with the commentaries Dinakari and Ramarudri, have been of decisive significance for the last few centuries as advanced introductions to this subject. The present work concentrates on inference in Karikavali, Muktavali and Dinakari, carefully divided into significant units according to the subject, and translates and interprets them. Its commentary makes use of (...) the primary interpretation in Sanskrit contained especially in the Ramarudri and Subodhini. The book begins with the Sanskrit texts of Karikavali and Muktavali; followed by English translation of these texts. Next is given the Sanskrit text of Dinakari which comments on the first two texts, followed by its English translation. Lastly, the book contains a commentary on all the texts included. (shrink)

Discussion of the uses of indicative conditionals. Reasons for holding that when the antecedent is true, the conditional has the same truth value as the consequent. Conditionals as ‘inference‐tickets’. Non‐interference conditionals: ‘Even if A, still C’. So‐called ‘biscuit conditionals’.

How should we reason in science? Jan Sprenger and Stephan Hartmann offer a refreshing take on classical topics in philosophy of science, using a single key concept to explain and to elucidate manifold aspects of scientific reasoning. They present good arguments and good inferences as being characterized by their effect on our rational degrees of belief. Refuting the view that there is no place for subjective attitudes in 'objective science', Sprenger and Hartmann explain the value of convincing evidence in terms (...) of a cycle of variations on the theme of representing rational degrees of belief by means of subjective probabilities (and changing them by Bayesian conditionalization). In doing so, they integrate Bayesian inference—the leading theory of rationality in social science—with the practice of 21st century science. Bayesian Philosophy of Science thereby shows how modeling such attitudes improves our understanding of causes, explanations, confirming evidence, and scientific models in general. It combines a scientifically minded and mathematically sophisticated approach with conceptual analysis and attention to methodological problems of modern science, especially in statistical inference, and is therefore a valuable resource for philosophers and scientific practitioners. (shrink)

The phrase ‘evaluative inference’ was used by Toulmin for ‘that form of inference by which we pass from factual reasons to an ethical conclusion’; and the phrase has been attacked by Hare in his review of Toulmin and in his book. I shall try to dig out some of the questions at issue in that discussion, but to do so without the help of this technical term, or of any other that I can avoid.

In mental action there is no motor output to be controlled and no sensory input vector that could be manipulated by bodily movement. It is therefore unclear whether this specific target phenomenon can be accommodated under the predictive processing framework at all, or if the concept of “active inference” can be adapted to this highly relevant explanatory domain. This contribution puts the phenomenon of mental action into explicit focus by introducing a set of novel conceptual instruments and developing a first (...) positive model, concentrating on epistemic mental actions and epistemic self-control. Action initiation is a functionally adequate form of self-deception; mental actions are a specific form of predictive control of effective connectivity, accompanied and possibly even functionally mediated by a conscious “epistemic agent model”. The overall process is aimed at increasing the epistemic value of pre-existing states in the conscious self-model, without causally looping through sensory sheets or using the non-neural body as an instrument for active inference. (shrink)

I argue that the accounts of inference recently presented (in this journal) by Paul Boghossian, John Broome, and Crispin Wright are unsatisfactory. I proceed in two steps: First, in Sects. 1 and 2, I argue that we should not accept what Boghossian calls the “Taking Condition on inference” as a condition of adequacy for accounts of inference. I present a different condition of adequacy and argue that it is superior to the one offered by Boghossian. More precisely, I point out (...) that there is an analog of Moore’s Paradox for inference; and I suggest that explaining this phenomenon is a condition of adequacy for accounts of inference. Boghossian’s Taking Condition derives its plausibility from the fact that it apparently explains the analog of Moore’s Paradox. Second, in Sect. 3, I show that neither Boghossian’s, nor Broome’s, nor Wright’s account of inference meets my condition of adequacy. I distinguish two kinds of mistake one is likely to make if one does not focus on my condition of adequacy; and I argue that all three—Boghossian, Broome, and Wright—make at least one of these mistakes. (shrink)

Causation is a macroscopic phenomenon. The temporal asymmetry displayed by causation must somehow emerge along with other asymmetric macroscopic phenomena like entropy increase and the arrow of radiation. I shall approach this issue by considering ‘causal inference’ techniques that allow causal relations to be inferred from sets of observed correlations. I shall show that these techniques are best explained by a reduction of causation to structures of equations with probabilistically independent exogenous terms. This exogenous probabilistic independence imposes a recursive order (...) on these equations and a consequent distinction between dependent and independent variables that lines up with the temporal asymmetry of causation. (shrink)

Arguably the most foundational principle in perception research is that our experience of the world goes beyond the retinal image; we perceive the distal environment itself, not the proximal stimulation it causes. Shape may be the paradigm case of such “unconscious inference”: When a coin is rotated in depth, we infer the circular object it truly is, discarding the perspectival ellipse projected on our eyes. But is this really the fate of such perspectival shapes? Or does a tilted coin retain (...) an elliptical appearance even when we know it’s circular? This question has generated heated debate from Locke and Hume to the present; but whereas extant arguments rely primarily on introspection, this problem is also open to empirical test. If tilted coins bear a representational similarity to elliptical objects, then a circular coin should, when rotated, impair search for a distal ellipse. Here, nine experiments demonstrate that this is so, suggesting that perspectival shapes persist in the mind far longer than traditionally assumed. Subjects saw search arrays of three-dimensional “coins,” and simply had to locate a distally elliptical coin. Surprisingly, rotated circular coins slowed search for elliptical targets, even when subjects clearly knew the rotated coins were circular. This pattern arose with static and dynamic cues, couldn’t be explained by strategic responding or unfamiliarity, generalized across shape classes, and occurred even with sustained viewing. Finally, these effects extended beyond artificial displays to real-world objects viewed in naturalistic, full-cue conditions. We conclude that objects have a remarkably persistent dual character: their objective shape “out there,” and their perspectival shape “from here.”. (shrink)

In this paper I provide empirical and theoretical considerations in favor of a non-inferential view of speech comprehension. On the view defended, we typically comprehend speech by perceiving or grasping apparently conveyed meanings directly rather than by inferring them from, say, linguistic principles and perceived phonemes. “Speech” is here used in the broad sense to refer not only to verbal expression, but also written messages, including Braille, and conventional signs and symbols, like emojis, a stop sign or a swastika. Along (...) the way I define what I mean by ‘inference’ and provide an account of what it means to say that we perceive apparently conveyed meanings. (shrink)

What exactly is reasoning? While debate on this question is ongoing, most philosophers seem to agree on at least the following: reasoning is a mental process operating on contents, which consists in adopting or revising some of your attitudes in light of others. In this paper, I argue that this characterisation is mistaken: there is no single mental phenomenon that satisfies both of these conditions. Instead, I characterise two distinct mental phenomena, which I call ‘deducing’, on the one hand, and (...) ‘reasoning’ or ‘inference’ on the other, to play each of these roles. Recognising this division of labour is essential to developing a better understanding of our rational economy. (shrink)

Peter Lipton argues that inference to the best explanation involves the selection of a hypothesis on the basis of its loveliness. I argue that in optimal cases of IBE we may be able to eliminate all but one of the hypotheses. In such cases we have a form of eliminative induction takes place, which I call ‘Holmesian inference’. I argue that Lipton’s example in which Ignaz Semmelweis identified a cause of puerperal fever better illustrates Holmesian inference than Liptonian IBE. I (...) consider in detail the conditions under which Holmesian inference is possible and conclude by considering the epistemological relations between Holmesian inference and Liptonian IBE.Keywords: Inference to the best explanation; Peter Lipton; Abduction; Holmesian inference; Eliminative induction. (shrink)

Much evidence has accumulated in favor of such a dual view of reasoning. There is however some vagueness in the way the two systems are characterized. Instead of a principled distinction, we are presented with a bundle of contrasting features - slow/fast, automatic/controlled, explicit/implicit, associationist/rule based, modular/central - that, depending on the specific dual process theory, are attributed more or less exclusively to one of the two systems. As Evans states in a recent review, “it would then be helpful to (...) have some clear basis for this distinction”; he also suggests that “we might be better off talking about type 1 and type 2 processes” rather than systems. We share the intuitions that drove the development of dual system theories. Our goal here is to propose in the same spirit a principled distinction between two types of inferences: ‘intuitive inference’ and ‘reflective inference’. We ground this distinction in a massively modular view of the human mind where metarepresentational modules play an important role in explaining the peculiarities of human psychological evolution. We defend the hypothesis that the main function of reflective inference is to produce and evaluate arguments occurring in interpersonal communication. This function, we claim, helps explain important aspects of reasoning. We review some of the existing evidence and argue that it gives support to this approach. (shrink)

To what extent is predictive processing enactivist? This overview of predictive processing and active inference offers an account of embodied exchange with the world that associates neuronal processing with inferring the causes of our sensations. Crucially, one of the most important causes of the sensorium is our own behaviour, which—perhaps counterintuitively—has to be inferred. The agenda—in active inference—is to link formal (mathematical) descriptions of dynamical systems to a description of active perception in terms of beliefs and goals. In short, it (...) tries to understand why and how we gather evidence for our own existence. There are several approaches to this sort of formulation. This chapter compares and contrasts a Helmholtzian or Kantian (bottom-up) approach—via perception—with the sort of (top-down) approaches offered by the statistical physics of self-organisation in sentient systems. (shrink)

In Philosophy without Intuitions, Herman Cappelen challenges the ‘almost universally accepted’ thesis of ‘Centrality’: ‘philosophers rely on intuitions as evidence for philosophical theories’. Cappelen takes there to be two arguments for Centrality and rejects both. According to the first, Centrality is supported by the way philosophers characterize key premises in their arguments as ‘intuitive’. Central to Cappelen’s rejection of this is his lengthy argument that philosophers’ ‘intuition’-talk is very hard to interpret, indeed often ‘meaningless’. I argue, in contrast, that this (...) talk is easy to interpret. The great mass of philosophers who would endorse Centrality mean by ‘intuition’ just what it ordinarily means: ‘immediate judgment, without reasoning or inference’. Cappelen claims further that philosophers’ ‘intuition’-talk, however it is interpreted, does not support Centrality. I argue that this talk, interpreted in the ordi.. (shrink)

Tourette syndrome (TS) has been associated with a rich set of symptoms that are said to be uncomfortable, unwilled, and effortful to manage. Furthermore, tics, the canonical characteristic of TS, are multifaceted, and their onset and maintenance is complex. A formal account that integrates these features of TS symptomatology within a plausible theoretical framework is currently absent from the field. In this paper, we assess the explanatory power of hierarchical generative modelling in accounting for TS symptomatology from the perspective of (...) active inference. We propose a fourfold analysis of sensory, motor, and cognitive phenomena associated with TS. In Section 1, we characterise tics as a form of action aimed at sensory attenuation. In Section 2, we introduce the notion of epistemic ticcing and describe such behaviour as the search for evidence that there is an agent (i.e., self) at the heart of the generative hierarchy. In Section 3, we characterise both epistemic (sensation-free) and nonepistemic (sensational) tics as habitual behaviour. Finally, in Section 4, we propose that ticcing behaviour involves an inevitable conflict between distinguishable aspects of selfhood; namely, between the minimal phenomenal sense of self—which is putatively underwritten by interoceptive inference—and the explicit preferences that constitute the individual’s conceptual sense of self. In sum, we aim to provide an empirically informed analysis of TS symptomatology under active inference, revealing a continuity between covert and overt features of the condition. (shrink)

This article presents and discusses one of the most prominent inferential strategies currently employed in cognitive neuropsychology, namely, reverse inference. Simply put, this is the practice of inferring, in the context of experimental tasks, the engagement of cognitive processes from locations or patterns of neural activation. This technique is notoriously controversial because, critics argue, it presupposes the problematic assumption that neural areas are functionally selective. We proceed as follows. We begin by introducing the basic structure of traditional “location-based” reverse inference (...) and discuss the influential lack of selectivity objection. Next, we rehearse various ways of responding to this challenge and provide some reasons for cautious optimism. The second part of the essay presents a more recent development: “pattern-decoding reverse inference”. This inferential strategy, we maintain, provides an even more convincing response to the lack of selectivity charge. Due to this and other methodological advantages, it is now a prominent component in the toolbox of cognitive neuropsychology. Finally, we conclude by drawing some implications for philosophy of science and philosophy of mind. (shrink)

In this article we examine obsessive compulsive disorder (OCD). We examine and reject two existing models of this disorder: the Dysfunctional Belief Model and the Inference‐Based Approach. Instead, we propose that the main distinctive characteristic of OCD is a hyperactive sub‐personal signal of being in error, experienced by the individual as uncertainty about his or her intentional actions (including mental actions). This signalling interacts with the anxiety sensitivities of the individual to trigger conscious checking processes, including speculations about possible harms. (...) We examine the implications of this model for the individual's capacity to control his or her thoughts. (shrink)

The debate between scientific realism and anti-realism remains at a stalemate, making reconciliation seem hopeless. Yet, important work remains: exploring a common ground, even if only to uncover deeper points of disagreement and, ideally, to benefit both sides of the debate. I propose such a common ground. Specifically, many anti-realists, such as instrumentalists, have yet to seriously engage with Sober's call to justify their preferred version of Ockham's razor through a positive account. Meanwhile, realists face a similar challenge: providing a (...) non-circular explanation of how their version of Ockham's razor connects to truth. The common ground I propose addresses these challenges for both sides; the key is to leverage the idea that everyone values some truths and to draw on insights from scientific fields that study scientific inference—namely, statistics and machine learning. This common ground also isolates a distinctively epistemic root of the irreconcilability in the realism debate. (shrink)

Background: Classical computability and complexity theory analyze how costly a computation is in time or space, assuming inputs are already encoded as finite strings. The knowledge-representation tradition recognizes that representation choices constrain inference—most notably through the expressiveness–tractability tradeoff—but focuses on the complexity of querying a fixed representation, not on whether certain representational resources are necessary for a task to be expressible at all. Meanwhile, deep learning systems exhibit systematic failures on compositional and multi-object reasoning, symbolic systems face the classical symbol-grounding (...) problem, and neuro-symbolic architectures lack a formal account of which representational resources are required for which tasks. -/- Objectives: I aim to develop a computability-theoretic framework that classifies computational tasks by their minimal representational requirements—an axis orthogonal to time–space complexity—thereby providing formal criteria for determining when connectionist, symbolic, or neuro-symbolic architectures are representationally adequate, or provably inadequate, for a given task. -/- Methods: I introduce the Hierarchical Representational Machine (HRM), which stratifies representational resources into four layers: Structured Input Space (L1), grounded in Type-2 Theory of Effectivity; Equivalence and Measurement (L2), formalized via computable quotient spaces and representational measurement theory; Formal Symbolic Representation (L3), providing compositional syntax with effective derivation; and Admissibility Constraints (L4), supplying decidable meta-level filters for safety, legality, and verification. For each layer, I define necessity schemas that identify structural conditions on tasks—invariance, unbounded compositionality, and hard admissibility—under which that layer is provably required. I establish separation results via diagonal and undecidability arguments, and introduce the meta-problem HRM-Classify with the minimal requirement operator Req(T). -/- Results: The main results are: (i) three necessity schemas identifying when specific layers are unavoidable; (ii) separation theorems establishing strict gaps between layer-restricted solvability classes—{L1} ⊊ {L1,L2}, {L3} ⊊ {L1,L2,L3}, and {L1,L2,L3} ⊊ {L1,L2,L3,L4} under external-standard semantics—demonstrating that these layers correspond to genuine computability-theoretic distinctions even for constant-output tasks; and (iii) a solvability classification via Req(T) with worked examples spanning object recognition, program verification, and autonomous driving that illustrate the full layer hierarchy. -/- Conclusions: HRM provides a formal vocabulary for diagnosing representational insufficiency in AI systems: distribution-shift brittleness is identified as missing invariance structure, systematic compositional failures as insufficient symbolic resources, and constraint violations as absent admissibility gates. The framework serves as a principled pre-architectural analysis tool that determines minimal representational commitments before algorithm selection. Because HRM addresses representational feasibility rather than computational efficiency, it complements existing frameworks such as PAC/VC theory, knowledge compilation, and category-theoretic approaches, and is applicable wherever the question "what must be representable?" precedes "how hard is inference?". (shrink)

Classical epistemic logic describes implicit knowledge of agents about facts and knowledge of other agents based on semantic information. The latter is produced by acts of observation or communication that are described well by dynamic epistemic logics. What these logics do not describe, however, is how significant information is also produced by acts of inference— and key axioms of the system merely postulate "deductive closure". In this paper, we take the view that all information is produced by acts, and hence (...) we also need a dynamic logic of inference steps showing what effort on the part of the agent makes a conclusion explicit knowledge. Strong omniscience properties of agents should be seen not as static idealizations, but as the result of dynamic processes that agents engage in. This raises two questions: (a) how to define suitable information states of agents and matching notions of explicit knowledge, (b) how to define natural processes over these states that generate new explicit knowledge. To this end, we use a static base from the existing awareness literature, extending it into a dynamic system that includes traditional acts of observation, but also adding and dropping formulas from the current ' awareness' set. We give a completeness theorem, and we show how this dynamics updates explicit knowledge. Then we extend our approach to multi-agent scenarios where awareness changes may happen privately. Finally, we mention further directions and related approaches. Our contribution can be seen as a ' dynamification' of existing awareness logics. (shrink)

When someone masters a skill, their performance looks to us like second nature: it looks as if their actions are smoothly performed without explicit, knowledge-driven, online monitoring of their performance. Contemporary computational models in motor control theory, however, are instructionist: that is, they cast skillful performance as a knowledge-driven process. Optimal motor control theory, as representative par excellence of such approaches, casts skillful performance as an instruction, instantiated in the brain, that needs to be executed—a motor command. This paper aims (...) to show the limitations of such instructionist approaches to skillful performance. We specifically address the question of whether the assumption of control-theoretic models is warranted. The first section of this paper examines the instructionist assumption, according to which skillful performance consists of the execution of theoretical instructions harnessed in motor representations. The second and third sections characterize the implementation of motor representations as motor commands, with a special focus on formulations from OMCT. The final sections of this paper examine predictive coding and active inference—behavioral modeling frameworks that descend, but are distinct, from OMCT—and argue that the instructionist, control-theoretic assumptions are ill-motivated in light of new developments in active inference. (shrink)

The main concepts of the free energy (FE) neuroscience developed by Karl Friston and colleagues parallel those of Freud's Project for a Scientific Psychology. In Hobson et al. ( 2014 ) these include an innate virtual reality generator that produces the fictive prior beliefs that Freud described as the primary process. This enables Friston's account to encompass a unified treatment—a complexity theory—of the role of virtual reality in both dreaming and mental disorder. In both accounts the brain operates to minimize (...) FE aroused by sensory impingements—including interoceptive impingements that report compliance with biological imperatives—and constructs a representation/model of the causes of impingement that enables this minimization. In Friston's account (variational) FE equals complexity minus accuracy, and is minimized by increasing accuracy and decreasing complexity. Roughly the brain (or model) increases accuracy together with complexity in waking. This is mediated by consciousness-creating active inference—by which it explains sensory impingements in terms of perceptual experiences of their causes. In sleep it reduces complexity by processes that include both synaptic pruning and consciousness/virtual reality/dreaming in REM. The consciousness-creating active inference that effects complexity-reduction in REM dreaming must operate on FE-arousing data distinct from sensory impingement. The most relevant source is remembered arousals of emotion, both recent and remote, as processed in SWS and REM on “active systems” accounts of memory consolidation/reconsolidation. Freud describes these remembered arousals as condensed in the dreamwork for use in the conscious contents of dreams, and similar condensation can be seen in symptoms. Complexity partly reflects emotional conflict and trauma. This indicates that dreams and symptoms are both produced to reduce complexity in the form of potentially adverse (traumatic or conflicting) arousals of amygdala-related emotions. Mental disorder is thus caused by computational complexity together with mechanisms like synaptic pruning that have evolved for complexity-reduction; and important features of disorder can be understood in these terms. Details of the consilience among Freudian, systems consolidation, and complexity-reduction accounts appear clearly in the analysis of a single fragment of a dream, indicating also how complexity reduction proceeds by a process resembling Bayesian model selection. (shrink)

The main currently unsolved problem in the theory of argumentation concerns the function of logic in argumentation and reasoning. The traditional view simply identified logic with the theory of reasoning. This view is still being echoed in older textbooks of formal logic. In a different variant, the same view is even codified in the ordinary usage of words such as ‘logic’, ‘deduction’, ‘inference’, etc. For each actual occurrence of these terms in textbooks of formal logic, there are hundreds of uses (...) of the same idioms to describe the feats of real or fictional detectives. I have called the idea reflected by this usage the “Sherlock Holmes conception of logic and deduction.” In the history of science, we find no less a thinker than Sir Isaac Newton describing his experimental method as one of analysis or resolution and claiming to have “deduced” at least some of his laws from the “phenomena.”. (shrink)

I examine and resolve an exegetical dichotomy between two main interpretations of Peirce’s theory of abduction, namely, the Generative Interpretation and the Pursuitworthiness Interpretation. According to the former, abduction is the instinctive process of generating explanatory hypotheses through a mental faculty called insight. According to the latter, abduction is a rule-governed procedure for determining the relative pursuitworthiness of available hypotheses and adopting the worthiest one for further investigation—such as empirical tests—based on economic considerations. It is shown that the Generative Interpretation (...) is inconsistent with a fundamental fact of logic for Peirce—i.e., abduction is a kind of inference—and the Pursuitworthiness Interpretation is flawed and inconsistent with Peirce’s naturalistic explanation for the possibility of science and his view about the limitations of classical scientific method. Changing the exegetical locus classicus from the logical form of abduction to insight and economy of research, I argue for the Unified Interpretation according to which abduction includes both instinctive hypotheses-generation and rule-governed hypotheses-ranking. I show that the Unified Interpretation is immune to the objections raised successfully against the Generative and the Pursuitworthiness interpretations. (shrink)

This paper is Part I of a trilogy that restates and further develops the comprehensive work on the ICB ( 'The Infinite Choice Barrier: A Structural Limit of Algorithmic Cognition' , AGI is Impossible Here is The Proof" (Schlereth, 2025)) , which separates the philosophical from the mathematical view, while expanding upon specific domains of the original proof. -/- We show that while algorithms can perfectly infer within a closed frame (“Inference”), they are structurally blind to step out of it (...) Using the transition from Newtonian to Einsteinian physics as an existence proof, we demonstrate that semantic innovation requires a primitive that invalidates the system’s own evaluation metric–a move no algorithm can execute without external intervention. The barrier is not empirical, but topological: an algorithmic map cannot act as the territory. We conclude that the future of intelligence can impossibly be the automation of judgment (AGI). The wall that this endeavor would have to take is iterally infinitely high (and wide), and invisible on top of that. However, there probably is a way to work with this restraint, but only when truly understanding what this barrier is. The ICB Theorem tries to deliver exactly that. ───────────────────────────────────────────── Stack context (added 2026-05-15): -/- • ICB I (this paper)— Conceptual diagnosis. Schlereth (2025), PhilPapers ID SCHTIC-15. • ICB II — Formal proof, triangulation, Coq appendix. Schlereth (2025), PhilPapers ID SCHTIC-16. • ICB III — Probabilistic case (P-BOSS, hallucination). Schlereth (2025), PhilPapers ID SCHTIC-17. • ICB IV — CSI architecture, General Cognitive Equation. Schlereth (2026), PhilPapers ID SCHAIN-8. • PTAC v1.0 — Coq machine-verified formalization. Schlereth (2026), Zenodo DOI 10.5281/zenodo.20195456 (GitHub repo: z7xt8zzjb5-prog/PTAC_v.1). ─────────────────────────────────────────────. (shrink)

In this paper we discuss the new Tweety puzzle. The original Tweety puzzle was addressed by approaches in non-monotonic logic, which aim to adequately represent the Tweety case, namely that Tweety is a penguin and, thus, an exceptional bird, which cannot fly, although in general birds can fly. The new Tweety puzzle is intended as a challenge for probabilistic theories of epistemic states. In the first part of the paper we argue against monistic Bayesians, who assume that epistemic states can (...) at any given time be adequately described by a single subjective probability function. We show that monistic Bayesians cannot provide an adequate solution to the new Tweety puzzle, because this requires one to refer to a frequency-based probability function. We conclude that monistic Bayesianism cannot be a fully adequate theory of epistemic states. In the second part we describe an empirical study, which provides support for the thesis that monistic Bayesianism is also inadequate as a descriptive theory of cognitive states. In the final part of the paper we criticize Bayesian approaches in cognitive science, insofar as their monistic tendency cannot adequately address the new Tweety puzzle. We, further, argue against monistic Bayesianism in cognitive science by means of a case study. In this case study we show that Oaksford and Chater’s (2007, 2008) model of conditional inference—contrary to the authors’ theoretical position—has to refer also to a frequency-based probability function. (shrink)

In pedagogical contexts and in everyday life, we often come to believe something because it would best explain the data. What is it about the explanatory endeavor that makes it essential to everyday learning and to scientific progress? There are at least two plausible answers. On one view, there is something special about having true explanations. This view is highly intuitive: it’s clear why true explanations might improve one’s epistemic position. However, there is another possibility—it could be that the process (...) of seeking, generating, or evaluating explanations itself puts one in a better epistemic position, even when the outcome of the process is not a true explanation. In other words, it could be that accurate explanations are beneficial, or it could be that high-quality explaining is beneficial, where there is something about the activity of looking for an explanation that improves our epistemic standing. The main goal of this paper is to tease apart these two possibilities, both theoretically and empirically, which we align with “Inference to the Best Explanation” and “Explaining for the Best Inference”, respectively. We also provide some initial support for EBI and identify promising directions for future research. (shrink)

The proposal that probabilistic inference and unconscious hypothesis testing are central to information processing in the brain has been steadily gaining ground in cognitive neuroscience and associated fields. One popular version of this proposal is the new theoretical framework of predictive processing or prediction error minimization, which couples unconscious hypothesis testing with the idea of ‘active inference’ and claims to offer a unified account of perception and action. Here we will consider one outstanding issue that still looms large at the (...) core of the PEM framework: the lack of a clear criterion for distinguishing conscious states from unconscious ones. In order to fulfill the promise of becoming a unifying framework for describing and modeling cognition, PEM needs to be able to differentiate between conscious and unconscious mental states or processes. We will argue that one currently popular view, that the contents of conscious experience are determined by the ‘winning hypothesis’, falls short of fully accounting for conscious experience. It ignores the possibility that some states of a system can control that system’s behavior even though they are apparently not conscious. What follows from this is that the ‘winning hypothesis’ view does not provide a complete account of the difference between conscious and unconscious states in the probabilistic brain. We show how this problem for the received view can be resolved by augmenting PEM with Daniel Dennett’s multiple drafts model of consciousness. This move is warranted by the similar roles that attention and internal competition play in both the PEM framework and the multiple drafts model. (shrink)

The enduring replication crisis in many scientific disciplines casts doubt on the ability of science to estimate effect sizes accurately, and in a wider sense, to self-correct its findings and to produce reliable knowledge. We investigate the merits of a particular countermeasure—replacing null hypothesis significance testing with Bayesian inference—in the context of the meta-analytic aggregation of effect sizes. In particular, we elaborate on the advantages of this Bayesian reform proposal under conditions of publication bias and other methodological imperfections that are (...) typical of experimental research in the behavioral sciences. Moving to Bayesian statistics would not solve the replication crisis single-handedly. However, the move would eliminate important sources of effect size overestimation for the conditions we study. (shrink)

Recent work by Robert Batterman and Alexander Rueger has brought attention to cases in physics in which governing laws at the base level “break down” and singular limit relations obtain between base- and upper-level theories. As a result, they claim, these are cases with emergent upper-level properties. This paper contends that this inference—from singular limits to explanatory failure, novelty or irreducibility, and then to emergence—is mistaken. The van der Pol nonlinear oscillator is used to show that there can be a (...) full explanation of upper-level properties entirely in base-level terms even when singular limits are present. Whether upper-level properties are emergent depends not on the presence of a singular limit but rather on details of the ampliative approximation methods used. The paper suggests that focusing on explanatory deficiency at the base level is key to understanding emergence in physics. (shrink)

An increasing number of arguments for causal pluralism invoke empirical psychological data. Different aspects of causal cognition—specifically, causal perception and causal inference—are thought to involve distinct cognitive processes and representations, and they thereby distinctively support transference and dependency theories of causation, respectively. We argue that this dualistic picture of causal concepts arises from methodological differences, rather than from an actual plurality of concepts. Hence, philosophical causal pluralism is not particularly supported by the empirical data. Serious engagement with cognitive science reveals (...) that the connection between psychological concepts of causation and philosophical notions is substantially more complicated than is traditionally presumed. (shrink)

One’s constitution—whether one is generous or miserly, temperate or intemperate, kind or mean, etc.—is beyond one’s control in significant respects. Yet one’s constitution affects how one acts. And how one acts affects one’s moral standing. The counterintuitive inference—the so-called problem of constitutive moral luck—is that one’s moral standing is, to some significant extent, beyond one’s control. This article grants the premises but resists the inference. It argues that one’s constitution should have no net impact on one’s moral standing. While a (...) bad constitution lowers the chance that one will act morally, it offers significant gains to moral standing should that chance materialize. A good constitution increases one’s chance of performing good acts but for correspondingly more modest gains. This effect should smooth out, and possibly eliminate, the expected impact of constitution on moral standing. (shrink)

I examine Howson’s alluring suggestion that Bayesianism, by supplying a logic of inductive inference—conditionalisation—solves the problem of induction. I draw on his historical heritage, especially Hume, Peirce, and Ramsey, to reconstruct the interpretation of the problem of induction that his remarks intimates. Roughly, it is that of how to amend the system with which one meets the world, in the light of new particulars. Unfortunately, his claim that conditionalisation constitutes a solution to this problem, I argue, fails by his own (...) lights, because it turns on the widely endorsed but nonetheless erroneous contention that a justification of conditionalisation qua rule of inference can be given independently from a justification of the priors. (shrink)

Recent discussions in the philosophy of psychology have examined the use and legitimacy of such notions as “representation”, “content”, “computation”, and “inference” within a scientific psychology. While the resulting assessments have varied widely, ranging from outright rejection of some or all of these notions to full vindication of their use, there has been notable agreement on the considerations deemed relevant for making an assessment. The answer to the question of whether the notion of, say, representational content may be admitted into (...) a scientific psychology has often been made to hinge upon whether the notion can be squared with our “ordinary” or “folk” style of psychological explanation, with its alleged commitment to the idiom of beliefs and desires. In this article, I proceed the other way around, starting with experimental psychology itself and asking whether such notions as the above play a legitimate role within a particular area of contemporary theory, the psychology of perception. My conclusion will be that especially the first three have a legitimate place in theories of perception, albeit one that differs from that ascribed to them in a significant portion of the philosophical literature. Along the way I develop a notion of noncognitive functional analysis, which separates the notion of contentful perceptual processing and perceptual representation from cognitive or conceptual content. (This paper has been reprinted, with stylistic revisions, in Perception and Cognition, Essays in the Philosophy of Psychology, Oxford, Clarendon Press, 2009, pp. 50-87.). (shrink)

What role do moment‐to‐moment comprehension processes play in visual attentional selection in picture stories? The current work uniquely tested the role of bridging inference generation processes on eye movements while participants viewed picture stories. Specific components of the Scene Perception and Event Comprehension Theory (SPECT) were tested. Bridging inference generation was induced by manipulating the presence of highly inferable actions embedded in picture stories. When inferable actions are missing, participants have increased viewing times for the immediately following critical image (Magliano, (...) Larson, Higgs, & Loschky, ). This study used eye‐tracking to test competing hypotheses about the increased viewing time: (a) Computational Load: inference generation processes increase overall computational load, producing longer fixation durations; (b) Visual Search: inference generation processes guide eye‐movements to pick up inference‐relevant information, producing more fixations. Participants had similar fixation durations, but they made more fixations while generating inferences, with that process starting from the fifth fixation. A follow‐up hypothesis predicted that when generating inferences, participants fixate scene regions important for generating the inference. A separate group of participants rated the inferential‐relevance of regions in the critical images, and results showed that these inferentially relevant regions predicted differences in other viewers’ eye movements. Thus, viewers’ event models in working memory affect visual attentional selection while viewing visual narratives. (shrink)