scholarly journals Towards a Symbolic Computational Philosophy (and Methodology!) for Mathematics

2013 ◽  
pp. 101-113
Author(s):  
Doron Zeilberger
Keyword(s):  
Computational Philosophy

Computational Philosophy

1990 ◽  
pp. 104-125
Author(s):  
W. Richard Stark
Keyword(s):  
Computational Philosophy

Computational Philosophy of Science.Paul Thagard

1990 ◽  
Vol 65 (1) ◽  
pp. 59-59
Author(s):  
Paul Thompson
Keyword(s):  
Computational Philosophy

scholarly journals Seven Properties of Self-Organization in the Human Brain

2020 ◽  
Vol 4 (2) ◽  
pp. 10
Author(s):  
Birgitta Dresp-Langley
Keyword(s):  
Adaptive Learning ◽  
Functional Organization ◽  
Dynamic Network ◽  
General Purpose ◽  
Self Organization ◽  
Functional Plasticity ◽  
Resonance Theory ◽  
Network Growth ◽  
Strong Artificial Intelligence ◽  
Computational Philosophy

The principle of self-organization has acquired a fundamental significance in the newly emerging field of computational philosophy. Self-organizing systems have been described in various domains in science and philosophy including physics, neuroscience, biology and medicine, ecology, and sociology. While system architecture and their general purpose may depend on domain-specific concepts and definitions, there are (at least) seven key properties of self-organization clearly identified in brain systems: (1) modular connectivity, (2) unsupervised learning, (3) adaptive ability, (4) functional resiliency, (5) functional plasticity, (6) from-local-to-global functional organization, and (7) dynamic system growth. These are defined here in the light of insight from neurobiology, cognitive neuroscience and Adaptive Resonance Theory (ART), and physics to show that self-organization achieves stability and functional plasticity while minimizing structural system complexity. A specific example informed by empirical research is discussed to illustrate how modularity, adaptive learning, and dynamic network growth enable stable yet plastic somatosensory representation for human grip force control. Implications for the design of “strong” artificial intelligence in robotics are brought forward.

Fast analysis of large antennas--A new computational philosophy

1980 ◽  
Vol 28 (3) ◽  
pp. 306-310 ◽  
Author(s):  
O. Bucci ◽  
G. Franceschetti ◽  
G. D'Elia
Keyword(s):  
Fast Analysis ◽  
Computational Philosophy

scholarly journals Computational Philosophy of Science

1989 ◽  
Vol 3 (6) ◽  
pp. 96 ◽  
Author(s):  
Paul Thagard ◽  
Peter Skiff
Keyword(s):  
Philosophy Of Science ◽  
Computational Philosophy

scholarly journals Computer Science and Metaphysics: A Cross-Fertilization

2019 ◽  
Vol 2 (1) ◽  
pp. 230-251 ◽  
Author(s):  
Daniel Kirchner ◽  
Christoph Benzmüller ◽  
Edward N. Zalta
Keyword(s):  
Computer Science ◽  
Computational Techniques ◽  
Computer Assisted ◽  
Modal Metaphysics ◽  
Philosophical Methods ◽  
Obvious Benefit ◽  
Computational Metaphysics ◽  
Computational Philosophy ◽  
Cross Fertilization

AbstractComputational 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.

Sign in / Sign up

Export Citation Format

Share Document