18 research outputs found
A new physarum learner for network structure learning from biomedical data
A novel structure learning algorithm for Bayesian Networks based on a Physarum Learner is presented. The
length of the connections within an initially fully connected Physarum-Maze is taken as the inverse Pearson
correlation coefficient between the connected nodes. The Physarum Learner then estimates the shortest indirect
paths between each pair of nodes. In each iteration, a score of the surviving edges is incremented.
Finally, the highest scored connections are combined to form a Bayesian Network. The novel Physarum
Learner method is evaluated with different configurations and compared to the LAGD Hill Climber showing
comparable performance with respect to quality of training results and increased time efficiency for large data
sets
Slime mould: The fundamental mechanisms of biological cognition
© 2018 Elsevier B.V. The slime mould Physarum polycephalum has been used in developing unconventional computing devices for in which the slime mould played a role of a sensing, actuating, and computing device. These devices treated the slime mould as an active living substrate, yet it is a self-consistent living creature which evolved over millions of years and occupied most parts of the world, but in any case, that living entity did not own true cognition, just automated biochemical mechanisms. To ârehabilitateâ slime mould from the rank of a purely living electronics element to a âcreature of thoughtsâ we are analyzing the cognitive potential of P. polycephalum. We base our theory of minimal cognition of the slime mould on a bottom-up approach, from the biological and biophysical nature of the slime mould and its regulatory systems using frameworks such as Lyon's biogenic cognition, Muller, di Primio-LengelerĆ modifiable pathways, Bateson's âpatterns that connectâ framework, Maturana's autopoietic network, or proto-consciousness and Morgan's Canon
Toward a formal theory for computing machines made out of whatever physics offers: extended version
Approaching limitations of digital computing technologies have spurred
research in neuromorphic and other unconventional approaches to computing. Here
we argue that if we want to systematically engineer computing systems that are
based on unconventional physical effects, we need guidance from a formal theory
that is different from the symbolic-algorithmic theory of today's computer
science textbooks. We propose a general strategy for developing such a theory,
and within that general view, a specific approach that we call "fluent
computing". In contrast to Turing, who modeled computing processes from a
top-down perspective as symbolic reasoning, we adopt the scientific paradigm of
physics and model physical computing systems bottom-up by formalizing what can
ultimately be measured in any physical substrate. This leads to an
understanding of computing as the structuring of processes, while classical
models of computing systems describe the processing of structures.Comment: 76 pages. This is an extended version of a perspective article with
the same title that will appear in Nature Communications soon after this
manuscript goes public on arxi
A cumulative index to the 1976 issues of a continuing bibliography on Aerospace Medicine and Biology
This publication is a cumulative index to the abstracts contained in Supplements 151 through 162 of Aerospace Medicine and Biology: A continuing bibliography. It includes three indexes - subject, personal author, and corporate source
A Biosymtic (Biosymbiotic Robotic) Approach to Human Development and Evolution. The Echo of the Universe.
In the present work we demonstrate that the current Child-Computer Interaction
paradigm is not potentiating human development to its fullest â it is associated with
several physical and mental health problems and appears not to be maximizing childrenâs
cognitive performance and cognitive development. In order to potentiate childrenâs
physical and mental health (including cognitive performance and cognitive development)
we have developed a new approach to human development and evolution.
This approach proposes a particular synergy between the developing human body,
computing machines and natural environments. It emphasizes that children should be
encouraged to interact with challenging physical environments offering multiple possibilities
for sensory stimulation and increasing physical and mental stress to the organism.
We created and tested a new set of computing devices in order to operationalize
our approach â Biosymtic (Biosymbiotic Robotic) devices: âAlbertâ and âCratusâ. In
two initial studies we were able to observe that the main goal of our approach is being
achieved. We observed that, interaction with the Biosymtic device âAlbertâ, in a natural
environment, managed to trigger a different neurophysiological response (increases
in sustained attention levels) and tended to optimize episodic memory performance in
children, compared to interaction with a sedentary screen-based computing device, in
an artificially controlled environment (indoors) - thus a promising solution to promote
cognitive performance/development; and that interaction with the Biosymtic device
âCratusâ, in a natural environment, instilled vigorous physical activity levels in children
- thus a promising solution to promote physical and mental health