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In recent years there has been increasing excitement concerning the potential of Artificial Intelligence to transform human society. This book addresses the leading edge of research in this area. The research described aims to address present incompatibilities of Human and Machine reasoning and learning approaches. According to the influential US funding agency DARPA (originator of the Internet and Self-Driving Cars) this new area represents the Third Wave of Artificial Intelligence (3AI, 2020s-2030s), and is being actively investigated in the US, Europe and China.The chapters of this book have been authored by a mixture of UK and other international specialists. Some of the key questions addressed by the Human-Like Computing programme include how AI systems might 1) explain their decisions effectively, 2) interact with human beings in natural language, 3) learn from small numbers of examples and 4) learn with minimal supervision. Solving such fundamental problems involves new foundational research in both the Psychology of perception and interaction as well as the development of novel algorithmic approaches in Artificial Intelligence.
This book investigates the fundamental challenge of bridging the gap between human cognitive processes and machine learning architectures to achieve the next generation of artificial intelligence. The authors, Nicholas Chater and Stephen Muggleton, curate a collection of research from international specialists to explore the 'Third Wave' of AI. By integrating insights from human psychology with novel algorithmic development, the text argues that future systems must move beyond brute-force data processing to achieve human-like reasoning, explanation, and efficient learning.
What You Will Find
Experts identify this collection as a vital resource for understanding the intersection of cognitive science and machine learning. Readers frequently note the technical density of the prose, which serves as a foundational text for researchers and practitioners in the field of Human-Like Computing.
Page Count:
544
Publication Date:
2021-09-20
Publisher:
Oxford University Press
ISBN-10:
0198862539
ISBN-13:
9780198862536
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