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Springer Universal Subgoaling and Chunking - AI Goal Hierarchies

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Description

This Springer research volume explores the automatic generation and learning of goal hierarchies through universal subgoaling and chunking techniques. The book traces the intellectual history of two parallel research paths that converge around foundational work in production systems and artificial intelligence, beginning with pioneering efforts at Carnegie-Mellon University in the 1970s. It documents the development of the Instructible Production System (IPS) project and examines how goal hierarchies can be automatically constructed and refined through learning mechanisms. The work represents a significant contribution to computer science and AI research, providing both theoretical foundations and practical insights into hierarchical problem-solving approaches. This volume is part of The Springer International Series in Engineering and Computer Science, positioning it within a respected academic publication series dedicated to advancing knowledge in computing disciplines.

Key Features

Part of The Springer International Series in Engineering and Computer Science, Volume 11, offering peer-reviewed academic research.

Explores automatic generation and learning of goal hierarchies through subgoaling and chunking methodologies in AI systems.

Documents historical development from Carnegie-Mellon University's Instructible Production System project and subsequent research evolution.

Addresses fundamental computer science and artificial intelligence topics relevant to hierarchical problem-solving and production systems.

Provides both theoretical frameworks and practical approaches for implementing automated goal hierarchy learning in computational systems.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
30 April 1986
Listed Since
15 December 2006

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