11,728 research outputs found
Computer Science and Metaphysics: A Cross-Fertilization
Computational philosophy is the use of mechanized computational techniques to
unearth philosophical insights that are either difficult or impossible to find
using traditional philosophical methods. Computational metaphysics is
computational philosophy with a focus on metaphysics. In this paper, we (a)
develop results in modal metaphysics whose discovery was computer assisted, and
(b) conclude that these results work not only to the obvious benefit of
philosophy but also, less obviously, to the benefit of computer science, since
the new computational techniques that led to these results may be more broadly
applicable within computer science. The paper includes a description of our
background methodology and how it evolved, and a discussion of our new results.Comment: 39 pages, 3 figure
Mechanizing Principia Logico-Metaphysica in Functional Type Theory
Principia Logico-Metaphysica contains a foundational logical theory for
metaphysics, mathematics, and the sciences. It includes a canonical development
of Abstract Object Theory [AOT], a metaphysical theory (inspired by ideas of
Ernst Mally, formalized by Zalta) that distinguishes between ordinary and
abstract objects.
This article reports on recent work in which AOT has been successfully
represented and partly automated in the proof assistant system Isabelle/HOL.
Initial experiments within this framework reveal a crucial but overlooked fact:
a deeply-rooted and known paradox is reintroduced in AOT when the logic of
complex terms is simply adjoined to AOT's specially-formulated comprehension
principle for relations. This result constitutes a new and important paradox,
given how much expressive and analytic power is contributed by having the two
kinds of complex terms in the system. Its discovery is the highlight of our
joint project and provides strong evidence for a new kind of scientific
practice in philosophy, namely, computational metaphysics.
Our results were made technically possible by a suitable adaptation of
Benzm\"uller's metalogical approach to universal reasoning by semantically
embedding theories in classical higher-order logic. This approach enables one
to reuse state-of-the-art higher-order proof assistants, such as Isabelle/HOL,
for mechanizing and experimentally exploring challenging logics and theories
such as AOT. Our results also provide a fresh perspective on the question of
whether relational type theory or functional type theory better serves as a
foundation for logic and metaphysics.Comment: 14 pages, 6 figures; preprint of article with same title to appear in
The Review of Symbolic Logi
Binary Mixtures of Particles with Different Diffusivities Demix
The influence of size differences, shape, mass and persistent motion on phase
separation in binary mixtures has been intensively studied. Here we focus on
the exclusive role of diffusivity differences in binary mixtures of equal-sized
particles. We find an effective attraction between the less diffusive
particles, which are essentially caged in the surrounding species with the
higher diffusion constant. This effect leads to phase separation for systems
above a critical size: A single close-packed cluster made up of the less
diffusive species emerges. Experiments for testing of our predictions are
outlined.Comment: 5 figures in main text, 8 figures in Supplemental Materia
Decision blocks: A tool for automating decision making in CLIPS
The human capability of making complex decision is one of the most fascinating facets of human intelligence, especially if vague, judgemental, default or uncertain knowledge is involved. Unfortunately, most existing rule based forward chaining languages are not very suitable to simulate this aspect of human intelligence, because of their lack of support for approximate reasoning techniques needed for this task, and due to the lack of specific constructs to facilitate the coding of frequently reoccurring decision block to provide better support for the design and implementation of rule based decision support systems. A language called BIRBAL, which is defined on the top of CLIPS, for the specification of decision blocks, is introduced. Empirical experiments involving the comparison of the length of CLIPS program with the corresponding BIRBAL program for three different applications are surveyed. The results of these experiments suggest that for decision making intensive applications, a CLIPS program tends to be about three times longer than the corresponding BIRBAL program
Boolean networks with robust and reliable trajectories
We construct and investigate Boolean networks that follow a given reliable
trajectory in state space, which is insensitive to fluctuations in the updating
schedule, and which is also robust against noise. Robustness is quantified as
the probability that the dynamics return to the reliable trajectory after a
perturbation of the state of a single node. In order to achieve high
robustness, we navigate through the space of possible update functions by using
an evolutionary algorithm. We constrain the networks to having the minimum
number of connections required to obtain the reliable trajectory. Surprisingly,
we find that robustness always reaches values close to 100 percent during the
evolutionary optimization process. The set of update functions can be evolved
such that it differs only slightly from that of networks that were not
optimized with respect to robustness. The state space of the optimized networks
is dominated by the basin of attraction of the reliable trajectory.Comment: 12 pages, 9 figure
Primary electron transfer kinetics in bacterial reaction centers with modified bacteriochlorophylls at tghe monomeric sites Ba, B
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