Natural Morphological Computation as Foundation of Learning to Learn in Humans, Other Living Organisms, and Intelligent Machines
Journal article, 2020

The emerging contemporary natural philosophy provides a common ground for the integrative view of the natural, the artificial, and the human-social knowledge and practices. Learning process is central for acquiring, maintaining, and managing knowledge, both theoretical and practical. This paper explores the relationships between the present advances in understanding of learning in the sciences of the artificial (deep learning, robotics), natural sciences (neuroscience, cognitive science, biology), and philosophy (philosophy of computing, philosophy of mind, natural philosophy). The question is, what at this stage of the development the inspiration from nature, specifically its computational models such as info-computation through morphological computing, can contribute to machine learning and artificial intelligence, and how much on the other hand models and experiments in machine learning and robotics can motivate, justify, and inform research in computational cognitive science, neurosciences, and computing nature. We propose that one contribution can be understanding of the mechanisms of ‘learning to learn’, as a step towards deep learning with symbolic layer of computation/information processing in a framework linking connectionism with symbolism. As all natural systems possessing intelligence are cognitive systems, we describe the evolutionary arguments for the necessity of learning to learn for a system to reach human-level intelligence through evolution and development. The paper thus presents a contribution to the epistemology of the contemporary philosophy of nature.

symbolism

morphological computing

information processing

cognition

info-computation

learning to learn

deep learning

connectionism

natural computing

artificial intelligence

learning

robotics

Author

Gordana Dodig Crnkovic

Chalmers, Computer Science and Engineering (Chalmers), Interaction design

Philosophies

2409-9287 (ISSN)

Vol. 5 3 17-32

Morphological Computing in Cognitive Systems (MORCOM@COGS)

Swedish Research Council (VR) (2015-05359), 2016-01-01 -- 2020-12-31.

Areas of Advance

Information and Communication Technology

Driving Forces

Sustainable development

Subject Categories

Learning

Philosophy

Information Science

Information Systemes, Social aspects

Computer Science

Roots

Basic sciences

DOI

10.3390/philosophies5030017

More information

Latest update

12/1/2021