Normative Formal Epistemology as Modelling

Oxford Studies in Epistemology Volume 6

10.1093/oso/9780198833314.001.0001 ◽

2019 ◽

Cited By ~ 1

Keyword(s):

Decision Theory ◽

A Priori ◽

Formal Epistemology ◽

Ethics Of Belief ◽

Naturalized Epistemology ◽

New Developments ◽

The Status ◽

Important Field ◽

Belief Justification

Oxford Studies in Epistemology is a biennial publication offering a regular snapshot of state-of-the-art work in this important field. Under the guidance of a distinguished editorial board composed of leading epistemologists in North America, Europe and Australasia, it publishes exemplary papers in epistemology, broadly construed. Topics within its purview include: (a) traditional epistemological questions concerning the nature of belief, justification, and knowledge, the status of skepticism, the nature of the a priori, etc.; (b) new developments in epistemology, including movements such as naturalized epistemology, feminist epistemology, social epistemology, and virtue epistemology, and approaches such as contextualism; (c) foundational questions in decision-theory; (d) confirmation theory and other branches of philosophy of science that bear on traditional issues in epistemology; (e) topics in the philosophy of perception relevant to epistemology; (f) topics in cognitive science, computer science, developmental, cognitive, and social psychology that bear directly on traditional epistemological questions; and (g) work that examines connections between epistemology and other branches of philosophy, including work on testimony, the ethics of belief, etc. Topics addressed in volume 6 include the nature of perceptual justification, intentionality, modal knowledge, credences, epistemic supererogation, epistemic and rational norms, expressivism, skepticism, and pragmatic encroachment. The various writers make use of a variety of different tools and insights, including those of formal epistemology and decision theory, as well as traditional philosophical analysis and argumentation.

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Vagueness, Kant and Topology: a Study of Formal Epistemology

Journal of Philosophical Logic ◽

10.1007/s10992-007-9064-0 ◽

2007 ◽

Vol 37 (2) ◽

pp. 141-168 ◽

Cited By ~ 4

Author(s):

Giovanni Boniolo ◽

Silvio Valentini

Keyword(s):

Formal Epistemology ◽

And Topology

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Troubles for Bayesian Formal Epistemology

Res Philosophica ◽

10.11612/resphil.1535 ◽

2017 ◽

Vol 94 (2) ◽

pp. 1-23 ◽

Cited By ~ 12

Author(s):

Terry Horgan

Keyword(s):

Formal Epistemology

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Formal Epistemology

Encyclopedia of Philosophy and the Social Sciences ◽

10.4135/9781452276052.n136 ◽

2013 ◽

Author(s):

Sebastian Sequoiah-Grayson

Keyword(s):

Formal Epistemology

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Computational Knowledge Representation in Cognitive Science

Epistemology & Philosophy of Science ◽

10.5840/eps201956355 ◽

2019 ◽

Vol 56 (3) ◽

pp. 138-152

Author(s):

Igor F. Mikhailov ◽

Keyword(s):

Knowledge Representation ◽

Cognitive Science ◽

Network Architecture ◽

Mathematical Theory ◽

Computational Approach ◽

Formal Epistemology ◽

The Social ◽

Parallel Network ◽

Substrate Independent ◽

Computational Systems

Cognitive research can contribute to the formal epistemological study of knowledge representation inasmuch as, firstly, it may be regarded as a descriptive science of the very same subject as that, of which formal epistemology is a normative one. And, secondly, the notion of representation plays a constitutive role in both disciplines, though differing therein in shades of its meaning. Representation, in my view, makes sense only being paired with computation. A process may be viewed as computational if it adheres to some algorithm and is substrate-independent. Traditionally, psychology is not directly determined by neuroscience, sticking to functional or dynamical analyses in the what-level and skipping mechanistic explanations in the how-level. Therefore, any version of computational approach in psychology is a very promising move in connecting the two scientific realms. On the other hand, the digital and linear computational approach of the classical cognitive science is of little help in this way, as it is not biologically realistic. Thus, what is needed there on the methodological level, is a shift from classical Turing-style computationalism to a generic computational theory that would comprehend the complicated architecture of neuronal computations. To this end, the cutting-edge cognitive neuroscience is in need of а satisfactory mathematical theory applicable to natural, particularly neuronal, computations. Computational systems may be construed as natural or artificial devices that use some physical processes on their lower levels as atomic operations for algorithmic processes on their higher levels. A cognitive system is a multi-level mechanism, in which linguistic, visual and other processors are built on numerous levels of more elementary operations, which ultimately boil down to atomic neural spikes. The hypothesis defended in this paper is that knowledge derives not only from an individual computational device, such as a brain, but also from the social communication system that, in its turn, may be presented as a kind of supercomputer of the parallel network architecture. Therefore, a plausible account of knowledge production and exchange must base on some mathematical theory of social computations, along with that of natural, particularly neuronal, ones.

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