Intelligence emerging : adaptivity and search in evolving neural systems / Keith L. Downing.

Format:

Book

Author/Creator:

Downing, Keith L., author.

Language:

English

Subjects (All):

Neural networks (Computer science).

Machine learning.

Experiential learning.

Genetic algorithms.

Adaptive computing systems.

Physical Description:

1 online resource (499 p.)

Edition:

1st ed.

Place of Publication:

Cambridge, Massachusetts ; London, England : The MIT Press, [2015]

Language Note:

English

Summary:

"Emergence--the formation of global patterns from solely local interactions--is a frequent and fascinating theme in the scientific literature both popular and academic. In this book, Keith Downing undertakes a systematic investigation of the widespread (if often vague) claim that intelligence is an emergent phenomenon. Downing focuses on neural networks, both natural and artificial, and how their adaptability in three time frames--phylogenetic (evolutionary), ontogenetic (developmental), and epigenetic (lifetime learning)--underlie the emergence of cognition. Integrating the perspectives of evolutionary biology, neuroscience, and artificial intelligence, Downing provides a series of concrete examples of neurocognitive emergence. Doing so, he offers a new motivation for the expanded use of bio-inspired concepts in artificial intelligence (AI), in the subfield known as Bio-AI. One of Downing's central claims is that two key concepts from traditional AI, search and representation, are key to understanding emergent intelligence as well. He first offers introductory chapters on five core concepts: emergent phenomena, formal search processes, representational issues in Bio-AI, artificial neural networks (ANNs), and evolutionary algorithms (EAs). Intermediate chapters delve deeper into search, representation, and emergence in ANNs, EAs, and evolving brains. Finally, advanced chapters on evolving artificial neural networks and information-theoretic approaches to assessing emergence in neural systems synthesize earlier topics to provide some perspective, predictions, and pointers for the future of Bio-AI"--MIT CogNet.

Contents:

Emergence

Search : the core of AI

Representations for search and emergence

Evolutionary algorithms

Artificial neural networks

Knowledge representation in neural networks

Search and representation in evolutionary algorithms

Evolution and development of the brain

Learning via synaptic tuning

Trial and error learning in neural networks

Evolving artificial neural networks

Recognizing emergent intelligence.

Notes:

Description based upon print version of record.

Includes bibliographical references and index.

OCLC-licensed vendor bibliographic record.

ISBN:

0-262-32867-4

0-262-32866-6

OCLC:

910623035