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
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.
It is still difficult to provide a meaningful definition that clearly describes intelligence and separates it as a concept. This difficulty makes discussion of other aspects of intelligence also difficult. It may be argued that intelligence enables people to get the best jobs or reach the highest levels of academic success. It could be argued that intelligence is a requirement for innovators, inventors.
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.
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.
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.
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.
This article will attempt to give a very brief overview of some of the technologies that make up the field of Artificial Intelligence.
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".