The term ‘Artificial Intelligence’ (AI) was coined by the American computer scientist John McCarthy for 'The Dartmouth Summer Research Project on Artificial Intelligence' in 1956. So in one sense the field is celebrating its fiftieth birthday this year. However its underlying themes can be traced back considerably further, to Greek and Roman mythology.
In this invited lecture I will review some of the pre-history of AI, starting with Homer's Iliad, continuing through medieval automata, the story of a chess-playing machine built in Austria in the 18th century and Rossum's Universal Robots to a discussion of the 'Turing Test' for intelligence. I will also look at early AI systems such as MENACE (the 'Machine Educable Noughts And Crosses Engine') and consider the contribution of AI pioneers such as John McCarthy, Marvin Minsky, Donald Michie and Allan Newell. I will describe the rise of powerful special-purpose AI systems (Expert Systems) in the 1980s and 1990s and their use in the first Gulf War and look at some notable examples of AI in Science Fiction. No prior knowledge of Artificial Intelligence will be assumed.
Professor Max Bramer has been Professor of Information Technology at the University of Portsmouth since 1989. He was a founder member of the British Computer Society's Specialist Group on Artificial Intelligence (SGAI) in the early 1980s and has been its Chairman for many years. He is one of the principal organisers of the AI-200x series of international conferences on Innovative Techniques and Applications of Artificial Intelligence, held in Cambridge, UK each year.
Professor Bramer is the UK representative on and current chair of the Technical
Committee on Artificial Intelligence of IFIP (the International Federation for
Information Processing). He is a member of the editorial board of the journal
Knowledge Based Systems and a member of the international Steering Committee
for the IEEE International Conference on Data Mining. He has lectured and written
extensively on topics in Artificial Intelligence for over 25 years. His current
principal areas of research are in data mining (in particular the automatic
derivation of classification rules from examples), case-based reasoning, model-based
approaches to diagnostic reasoning and methodologies for knowledge engineering.