The BCS Machine Intelligence Competition
During an after-dinner talk at an early British Computer
Society conferences, Rick Magaldi from British Airways
discussed the progress of Machine Intelligence in terms of
the progress of human flight. Flight has been mastered in
a way not yet paralleled by the emergence of machine
intelligence. At one point Rick discussed one of the
significant developments in the desire to fly as being
when learned people started to confidently but usually
disastrously, throw themselves off buildings. The
consensus at the conference was that within AI, we have
not really got to the stage where we are throwing
ourselves off buildings. This is about to change. The SGAI
(with AKRI) have decided to give people an opportunity to
hurl themselves into the void, risking public ridicule and
career stagnation to show what they have really achieved
in the development of Machine Intelligence. This
competition will put on show real systems working in real
time. It is hoped that the competition and the
competitors, over several years, will provide a new
interest and visible improvements in the development of
machine intelligence.
The competition will rely on people being open about
developments, no matter how small these may appear. It
will also serve as an opportunity to see what others can
achieve and could prove a valuable source of ideas.
Read about, and enter, the
competition here.
Machine Intelligence
From Fuzzy Logic to Logic
Fuzzy logic enables a computer to make decisions which
care more in line with the sort of decisions which a human
would make. Computer logic is rigorous and deterministic
and relates to finite states and numbering systems.
Computer logic marks distinct boundaries between any
states. For instance, given various weather conditions to
process such as, stormy, rainy, cloudy, sunny, ordinary
logic would assign one of these values to any weather
condition being observed. People however would recognise
all sorts of shades in between theses states such as dull
or drizzle etc. This is exactly what fuzzy logic can do.
What is more impressive is that fuzzy logic offers a way
of processing these decisions so that a final result is
still correct.
Read more about Fuzzy Logic here
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Intelligent Homes
Originally to investigate how much the system could learn
about human occupancy patterns by using mainly simple
movement sensors as input. The main function of the system
was to try to establish how many people were in each room
at any one time (occupant location monitor). This was done
by reference to a short term memory of sensor data and
heuristics to detect and correct errors in reasoning when
they occurred. The function of long term memory was to try
to predict how many people were likely to be in any room
in the near future and to predict the general occupancy
pattern at the start of each day. This information was
used to influence the decisions made by the short term
occupancy location monitor.
Read more about Intelligent
Homes here +....
Experts and Expert Systems
An expert system is a computer system that emulates the
decision-making ability of a human expert. Expert systems
are designed to solve complex problems by reasoning about
knowledge, like an expert, and not by following the
procedure of a developer as is the case in conventional
programming.
Read more about Experts and Expert Systems here
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Machine Memory
Unlike the case with human systems, the construction and
operation of machine memory is fully understood. This
means that models are not needed to simulate the way
machine memory works. Models of human memory however, are
used to try to equip machines with human like properties.
The need for memory models for machines is therefore to
help implement human like characteristics using artificial
or man made devices and systems.
Read more about Machine memory here
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Technology
This article will attempt to give a very brief overview
of some of the technologies that make up the field of
Artificial Intelligence.
Read more about Technology here
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Steve Grand
Steve Grand OBE is a British computer scientist and
roboticist. He was the creator and lead programmer of the
Creatures artificial life simulation, which he discussed
in his first book Creation: Life and how to make it, a
finalist for the 2001 Aventis Prize for Science Books. He
is also an Officer of the Most Excellent Order of the
British Empire, which he received in 2000. Grand’s project
from 2001-2006 was the building of an artificial robot
baby orang-utan, with the intention of having it learn as
a human baby would. This is documented in his book Growing
up with Lucy. Steve is presently working on a successor to
Creatures (but not called that). His aim is the same as it
was for Creatures, to make the closest thing to real
virtual life so far "not something that looks like it’s
alive and intelligent but something that really is".
Read more about Steve Grand’s work here
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