Computational philosophy in search of boundaries between object and method

The main goal of this paper is to point out a number of methodological difficulties faced by the supporters of different kinds of philosophical computationalism in the formation of their conceptual apparatus. The text examines the beliefs underlying physicalist panсomputationalism, as well as some inaccuracies in the classification of the concept of computation. Particular attention is paid to the principles of hierarchical correlation that underlie social neurosciences that actively use computational methods.

Seven Properties of Self-Organization in the Human Brain

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.

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.

Research of Basic Framework Construction for Computational Philosophy

The basic framework of computational philosophy has been established in this paper: core, innovation, system and methodology. The core is to seek unified theory of computation (UTC), which is the “hard core” in the research program of computational philosophy; the main purpose of innovation is to provide new research methods of philosophy for various computational theories, innovation is the most characteristic in computational philosophy, and is also the key for computational philosophy to establish its status in philosophy; its system is based on innovation research, and explains, models and provides solutions for traditional and new problems via the concepts, methods, tools and techniques of computation; methodology explains concepts, principles and methods in the computational discipline as well as other related disciplines to build the framework of meta-theoretical analysis based on innovation research.