Seminar by Roger Kingdon
Iterative Dialectic Engine for Automated Learning (IDEAL)
Roger Kingdon
Dstl, Oxford, United Kingdom
Date: Tuesday, November 10, 2009
Time: 11:00 AM
Venue: CS103.
Abstract:
IDEAL is a high-level description of how humans learn, also applicable to the design of learning algorithms for automated computing machines. In this talk I outline three derivations of the IDEAL architecture, summarise its key capabilities, and show that IDEAL is a persuasive model of human personality types. For further reading please refer to my recent book, 'Principia Intellegentia - The principles governing human and machine intelligence' (Allied Publishers, New Delhi, 2009).
About The Speaker:
Roger Kingdon is a computational physicist with over 20 years of postdoctoral experience in the theory and modelling of a wide range of physical systems using both conventional and novel techniques. He has 28 publications in the open literature and he is a named author on 47 other unclassified reports. In addition he has have maintained a strong spare-time interest in artificial intelligence which has resulted in the development of a novel cognitive architecture known as 'IDEAL', and a book, 'Principia Intellegentia: The principles governing human and machine intelligence' (Allied Publishers 2009). Roger has just completed a one-year MSc in Advanced Computing at Imperial College, London, and is visiting India for 3 months prior to returning to his post in UK government research.