Associative Learning for a Robot Intelligence

Some believe that artificial intelligence is undergoing a paradigm shift. There are undoubtedly several competing ideas and ideals. Neural networks and dynamic systems are offered as alternatives to the information processing and digital computer models of the brain. The reader is asked to decide between symbolic and subsymbolic, between algorithmic and nonalgorithmic, and between information processing and interactive systems. Even in the short distance travelled in this book, associative learning is seen to embrace both sides of these dichotomies.

Summary

A study of associative learning for a robot intelligence. It proposes that within an appropriate organization, associative learning can be embodied in a robot to realize a human-like intelligence, which sets its own goals, exhibits unique unformalizable behaviour and has no hidden homunculi.

Product details

• Authors: John H Andreae, John H (Univ Of Canterbury Andreae, John H. Andreae, Andreae John H
• Publisher: Imperial College Press
• Languages: English
• Product format: Hardback
• Released: 25.09.1998
• EAN: 9781860941320
• ISBN: 978-1-86094-132-0
• No. of pages: 360
• Dimensions: 225 mm x 162 mm x 24 mm
• Weight: 626 g
• Series: Artificial Intelligence
• Subject: Natural sciences, medicine, IT, technology > IT, data processing > IT