Computational evolution of neural and morphological development : towards evolutionary developmental artificial intelligence / Yaochu Jin.
2023
TA347.E96
Linked e-resources
Linked Resource
Online Access
Concurrent users
Unlimited
Authorized users
Authorized users
Document Delivery Supplied
Can lend chapters, not whole ebooks
Details
Title
Computational evolution of neural and morphological development : towards evolutionary developmental artificial intelligence / Yaochu Jin.
Author
Jin, Yaochu, 1966- author.
ISBN
9789819918546 (electronic bk.)
9819918545 (electronic bk.)
9789819918539
9819918537
9819918545 (electronic bk.)
9789819918539
9819918537
Published
Singapore : Springer, 2023.
Language
English
Description
1 online resource (304 pages) : illustrations (black and white, and color).
Item Number
10.1007/978-981-99-1854-6 doi
Call Number
TA347.E96
Dewey Decimal Classification
006.3/823
Summary
This book provides a basic yet unified overview of theory and methodologies for evolutionary developmental systems. Based on the authors extensive research into the synergies between various approaches to artificial intelligence including evolutionary computation, artificial neural networks, and systems biology, it also examines the inherent links between biological intelligence and artificial intelligence. The book begins with an introduction to computational algorithms used to understand and simulate biological evolution and development, including evolutionary algorithms, gene regulatory network models, multi-cellular models for neural and morphological development, and computational models of neural plasticity. Chap. 2 discusses important properties of biological gene regulatory systems, including network motifs, network connectivity, robustness and evolvability. Going a step further, Chap. 3 presents methods for synthesizing regulatory motifs from scratch and creating more complex regulatory dynamics by combining basic regulatory motifs using evolutionary algorithms. Multi-cellular growth models, which can be used to simulate either neural or morphological development, are presented in Chapters 4 and 5. Chap. 6 examines the synergies and coupling between neural and morphological evolution and development. In turn, Chap. 7 provides preliminary yet promising examples of how evolutionary developmental systems can help in self-organized pattern generation, referred to as morphogenetic self-organization, highlighting the great potentials of evolutionary developmental systems. Finally, Chap. 8 rounds out the book, stressing the importance and promise of the evolutionary developmental approach to artificial intelligence. Featuring a wealth of diagrams, graphs and charts to aid in comprehension, this book offers a valuable asset for graduate students, researchers and practitioners who are interested in pursuing a different approach to artificial intelligence.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Description based on print version record.
Series
Natural computing series.
Available in Other Form
Computational evolution of neural and morphological development.
Linked Resources
Online Access
Record Appears in
Online Resources > Ebooks
All Resources
All Resources
Table of Contents
Computational Models of Evolution and Development
Analysis of Gene Regulatory Networks
Evolutionary Synthesis of Gene Regulatory Dynamics
Evolution of Morphological Development
Evolution of Neural Development
Computational Brain-Body Co-Evolution
Evolutionary Morphogenetic Self-Organization of Swarm Robots
Towards Evolutionary Developmental Systems.
Analysis of Gene Regulatory Networks
Evolutionary Synthesis of Gene Regulatory Dynamics
Evolution of Morphological Development
Evolution of Neural Development
Computational Brain-Body Co-Evolution
Evolutionary Morphogenetic Self-Organization of Swarm Robots
Towards Evolutionary Developmental Systems.