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An AGI Brain for a Robot is the first and only book to give a detailed account and practical demonstration of an Artificial General Intelligence (AGI). Sections teach readers how to design and implement a brain in fast parallel hardware and embody it in the head of a robot moving in the real world. Associative learning is shown to be a powerful technique for novelty seeking, language learning, and planning. This book is for neuroscientists, robot designers, psychologists, philosophers and anyone curious about the evolution of the human brain and its specialized functions.
The overarching message of this book is that an AGI, as the brain of a robot, is within our grasp and would work like our own brains. The featured brain, called PP, is not a computer program. Instead, PP is a collection of networks of associations built from J. A. Fodor’s modules and the author’s groups. The associations are acquired by intimate interaction between PP in its robot body and the real world. Simulations of PP in one of two robots in a simple world demonstrate PP learning from the second robot, which is under human control.
- Explains how to design and implement a robot brain with real-world functions
- Describes fast parallel hardware for an AGI brain
- Exhibits free will, language learning, working memory and planning
- Introduces multiple context associative learning using modules and groups
- Provides a Java computer program and output data files via a companion website
Anyone interested in neuroscience, psychology, philosophy, artificial intelligence or robotics. No special knowledge is required.
1. Brain, Body and World
3. Interacting with PP
4. Learning to Take Turns
5. No Approval from Teacher
6. Experiments from the Past
1. Squashes in First Interaction
3. Excerpts from the Interactions
4. PP program and Architecture
- No. of pages:
- © Academic Press 2021
- 1st March 2021
- Academic Press
- Paperback ISBN:
Dr. Andreae obtained his PhD from Imperial College, London University in 1955. His research in Artificial Intelligence began at Standard Telecommunication Laboratories, Harlow, Essex, and he published a paper on his first learning machine, STeLLA, in 1963. In 1966 he moved from England to the Department of Electrical Engineering, University of Canterbury in Christchurch, NZ, where he continued his research and invented his second learning machine, PurrPuss, later shortened to PP. He has continued the research during retirement. Dr. Andreae has previously written two books on his research: Thinking with the Teachable Machine (Academic Press, 1977) and Associative Learning for a Robot Intelligence (Imperial College Press, 1998).
Formerly, Department of Electrical and Computer Engineering, University of Canterbury, Christchurch, New Zealand, Life Senior Member, IEEE
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