Course : the organisation |
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Course : the subject : the web and the New Media, some context, History |
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Next Monday Discussion : MacOSX and the first lab : Survival Kit |
ABSTRACT:
It can be demonstrated on system theoretical grounds that any system which learns
to perform many behavioural features with limited information handling resources
is constrained within a set of bounds called the recommendation architecture
by the requirement to find a compromise between the need to conserve physical
information handling resources and the need to learn without severe interference
with earlier learning.
Overall architecture, the definition of modules and components, and even device
algorithms are all constrained, with the severity of the constraints increasing
as the ratio of features to resources increases. Algorithms widely used in artificial
neural networks cannot be used in some major subsystems of the recommendation
architecture.
There are strong resemblances between the physical forms of a system within
the recommendation architecture bounds and the physiology of the human brain
including separations between and functions of the cortex, hippocampus, thalamus,
basal ganglia, cerebellum, hypothalamus and amygdala; the internal organization
of the cortex into layers, columns and areas; and the topology and synaptic
algorithms of neurons. Detailed psychological observations of a wide range of
cognitive phenomena, including semantic, episodic, working and procedural memory;
processes such as arithmetic; the deficits resulting from physical damage; and
sleep with dreaming can be modelled in a physiologically plausible manner by
a system within the recommendation architecture bounds.
Learning can be bootstrapped from experience with minimal and plausible a priori
information. Many phenomena labelled "conscious" can be modelled in
terms of physiology. Electronic systems within the recommendation architecture
bounds confirm the capabilities of the architecture and point the way to implementation
of systems with human like cognitive capabilities.
BIO:
Andrew was employed by Nortel Networks as a system designer and architect in
the design of extremely complex real time control telecommunications systems
from 1969 to 1999, and participated in successful projects to design and introduce
commercially successful state of the art systems with up to 20 million lines
of code and custom integrated circuit based hardware.
While still employed as a system architect, he wrote a book on understanding
the brain as a system, introducing a novel cognitive architecture. He subsequently
obtained a US patent for system architectures which can learn to manage a complex
telecommunications network based on the cognitive architecture. Since 1999 he
has been full time in academic research into cognitive systems, most recently
as a research fellow at the Australian National University.
His new book, "A Systems Architecture Approach to the Brain: from Neurons
to Consciousness", was published December 12th 2005 and will be introduced
at this seminar.