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Biologically Inspired Approaches to Advanced Information Technology

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Cover of 'Biologically Inspired Approaches to Advanced Information Technology'

Table of Contents

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    Book Overview
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    Chapter 1 Object-Oriented Specification of Complex Bio-computing Processes: A Case Study of a Network of Proteolytic Enzymes
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    Chapter 2 Analysis of Responses of Complex Bionetworks to Changes in Environmental Conditions
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    Chapter 3 Experimental Molecular Evolution Showing Flexibility of Fitness Leading to Coexistence and Diversification in Biological System
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    Chapter 4 Echo State Networks and Self-Prediction
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    Chapter 5 Learning Bayesian Networks by Lamarckian Genetic Algorithm and Its Application to Yeast Cell-Cycle Gene Network Reconstruction from Time-Series Microarray Data
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    Chapter 6 Towards Cortex Sized Attractor ANN
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    Chapter 7 Biologically Inspired Reinforcement Learning: Reward-Based Decomposition for Multi-goal Environments
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    Chapter 8 Dynamic Self-Assembly and Computation: From Biological to Information Systems
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    Chapter 9 Implementation and Evaluation of a System to Support Human Relationship Formation in Networked Virtual Space
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    Chapter 10 Biologically Plausible Speech Recognition with LSTM Neural Nets
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    Chapter 11 Spatial Tangible User Interfaces for Cognitive Assessment and Training
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    Chapter 12 Biologically Inspired Computer Virus Detection System
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    Chapter 13 Explaining Low-Level Brightness-Contrast Illusions Using Disinhibition
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    Chapter 14 Autonomous Acquisition of the Meaning of Sensory States Through Sensory-Invariance Driven Action
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    Chapter 15 Characterizing the Firing Properties of an Adaptive Analog VLSI Neuron
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    Chapter 16 Embryonic Machines That Divide and Differentiate
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    Chapter 17 Artificial Cellular Division by Self-Inspection
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    Chapter 18 A Hardware Implementation of a Network of Functional Spiking Neurons with Hebbian Learning
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    Chapter 19 A Study on Designing Robot Controllers by Using Reinforcement Learning with Evolutionary State Recruitment Strategy
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    Chapter 20 Movement Generation and Control with Generic Neural Microcircuits
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    Chapter 21 Efficiency and Task Allocation in Prey Retrieval
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    Chapter 22 Anatomy and Physiology of an Artificial Vision Matrix
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    Chapter 23 An Adaptive Mechanism for Epidemic Communication
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    Chapter 24 The Blob Division
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    Chapter 25 Distributed Central Pattern Generator Model for Robotics Application Based on Phase Sensitivity Analysis
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    Chapter 26 Ant-Based Approach to Mobile Agent Traversal
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    Chapter 27 An Ant Inspired Technique for Storage Area Network Design
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    Chapter 28 Media Streaming on P2P Networks with Bio-inspired Cache Replacement Algorithm
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    Chapter 29 An Artificial Immune System Approach to Misbehavior Detection in Mobile Ad Hoc Networks
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    Chapter 30 Scalable and Robust Scheme for Data Gathering in Sensor Networks
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    Chapter 31 Biologically Inspired Image Compression in Biomedical High-Throughput Screening
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    Chapter 32 Naïve Algorithms for Keyphrase Extraction and Text Summarization from a Single Document Inspired by the Protein Biosynthesis Process
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    Chapter 33 Biologically Motivated Trainable Selective Attention Model Using Adaptive Resonance Theory Network
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    Chapter 34 Searching for a Practical Evidence of the No Free Lunch Theorems
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    Chapter 35 How Collective Intelligence Emerge in Complex Environment?
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    Chapter 36 The Genealogy of Biomimetics: Half a Century’s Quest for Dynamic IT
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Title
Biologically Inspired Approaches to Advanced Information Technology
Published by
Springer, Berlin, Heidelberg, January 2004
DOI 10.1007/b101281
ISBNs
978-3-54-023339-8, 978-3-54-027835-1
Editors

Auke Jan Ijspeert, Masayuki Murata, Naoki Wakamiya

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X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 4%
Unknown 23 96%
Readers by discipline Count As %
Computer Science 1 4%
Unknown 23 96%