Special Issue "Logic and Science"

A special issue of Philosophies (ISSN 2409-9287).

Deadline for manuscript submissions: closed (15 November 2020).

Special Issue Editor

Dr. Fabien Paillusson
Website
Guest Editor
School of Maths & Physics, University of Lincoln, LN6 7TS Lincoln, UK
Interests: Theoretical and Computational modelling; the Foundations of Physics; Physics and Maths Education; AI (Machine Learning and Automated Reasoning); Logic and the Philosophy of Science

Special Issue Information

Dear Colleagues,

In his book Probability Theory: The Logic of Science, E.T. Jaynes developed the compelling thesis that probability theory constituted an overarching logical framework applicable to all known sciences at the time, ranging from physics to sociology. From the point of view of the philosophy of science, one may take issue with the take-home message, i.e., probability theory as the only logic of science. Firstly, one may ask how this view fares compared to the understanding of science developed by the philosophical tradition initiated by T. Kuhn and his successors. Second, is “probability theory as the logic of science” to be understood as a prescriptive or descriptive claim? If the proposition is to be prescriptive, on what grounds can one support, or instead challenge, this prescription? If, however, it is to be descriptive, is it supported by the contemporary practice of science or by historical accounts? Third, one may note that probability theory itself refers to propositional logic: a probabilistic proposition can be true or false. Furthermore, logic itself can be construed as a science; does this mean that probability theory can explain itself? Fourth, even if probability theory were to be common (by prescription or description) to all scientific disciplines at the stages where inferences are needed, it remains that many successful theories are not framed in a probabilistic manner and usually rest on a logic of a different kind, closer to first-order logic in nature. Within this more focused context, what can be said about the logic of individual theories? For example, is the logic of General Relativity comparable to the logic of, say, Reaction Kinetics? More generally, is there any logical “thread” (e.g., entailment) relating one theory (or even a discipline) to another? Finally, when assessing the virtues of an individual scientific theory, are there any identifiable logical constraints (e.g., self-consistency is a commonly advocated one) that it must satisfy for it to be taken seriously or widely accepted by the corresponding scientific community?

By addressing the aforementioned concerns or related questions, this Special Issue of Philosophies aims to bring together logic and philosophy of science in an original and contemporary light.

Dr. Fabien Paillusson
Guest Editor

Manuscript Submission Information

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Keywords

  • Science
  • Epistemology
  • Logic
  • Probability
  • Bayesianism
  • Supervenience
  • Theory
  • Metaphysics
  • Emergence

Published Papers (2 papers)

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Research

Open AccessArticle
The P–T Probability Framework for Semantic Communication, Falsification, Confirmation, and Bayesian Reasoning
Philosophies 2020, 5(4), 25; https://doi.org/10.3390/philosophies5040025 - 02 Oct 2020
Abstract
Many researchers want to unify probability and logic by defining logical probability or probabilistic logic reasonably. This paper tries to unify statistics and logic so that we can use both statistical probability and logical probability at the same time. For this purpose, this [...] Read more.
Many researchers want to unify probability and logic by defining logical probability or probabilistic logic reasonably. This paper tries to unify statistics and logic so that we can use both statistical probability and logical probability at the same time. For this purpose, this paper proposes the P–T probability framework, which is assembled with Shannon’s statistical probability framework for communication, Kolmogorov’s probability axioms for logical probability, and Zadeh’s membership functions used as truth functions. Two kinds of probabilities are connected by an extended Bayes’ theorem, with which we can convert a likelihood function and a truth function from one to another. Hence, we can train truth functions (in logic) by sampling distributions (in statistics). This probability framework was developed in the author’s long-term studies on semantic information, statistical learning, and color vision. This paper first proposes the P–T probability framework and explains different probabilities in it by its applications to semantic information theory. Then, this framework and the semantic information methods are applied to statistical learning, statistical mechanics, hypothesis evaluation (including falsification), confirmation, and Bayesian reasoning. Theoretical applications illustrate the reasonability and practicability of this framework. This framework is helpful for interpretable AI. To interpret neural networks, we need further study. Full article
(This article belongs to the Special Issue Logic and Science)
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Open AccessArticle
The Limits of Classical Extensional Mereology for the Formalization of Whole–Parts Relations in Quantum Chemical Systems
Philosophies 2020, 5(3), 16; https://doi.org/10.3390/philosophies5030016 - 13 Aug 2020
Abstract
This paper examines whether classical extensional mereology is adequate for formalizing the whole–parts relation in quantum chemical systems. Although other philosophers have argued that classical extensional and summative mereology does not adequately formalize whole–parts relation within organic wholes and social wholes, such critiques [...] Read more.
This paper examines whether classical extensional mereology is adequate for formalizing the whole–parts relation in quantum chemical systems. Although other philosophers have argued that classical extensional and summative mereology does not adequately formalize whole–parts relation within organic wholes and social wholes, such critiques often assume that summative mereology is appropriate for formalizing the whole–parts relation in inorganic wholes such as atoms and molecules. However, my discussion of atoms and molecules as they are conceptualized in quantum chemistry will establish that standard mereology cannot adequately fulfill this task, since the properties and behavior of such wholes are context-dependent and cannot simply be reduced to the summative properties of their parts. To the extent that philosophers of chemistry have called for the development of an alternative mereology for quantum chemical systems, this paper ends by proposing behavioral mereology as a promising step in that direction. According to behavioral mereology, considerations of what constitutes a part of a whole is dependent upon the observable behavior displayed by these entities. Thus, relationality and context-dependence are stipulated from the outset and this makes behavioral mereology particularly well-suited as a mereology of quantum chemical wholes. The question of which mereology is appropriate for formalizing the whole–parts relation in quantum chemical systems is relevant to contemporary philosophy of chemistry, since this issue is related to the more general questions of the reducibility of chemical wholes to their parts and of the reducibility of chemistry to physics, which have been of central importance within the philosophy of chemistry for several decades. More generally, this paper puts contemporary discussions of mereology within the philosophy of chemistry into a broader historical and philosophical context. In doing so, this paper also bridges the gap between formal mereology, conceived as a branch of formal ontology, and “applied” mereology, conceived as a branch of philosophy of science. Full article
(This article belongs to the Special Issue Logic and Science)
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