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Biologically Inspired Approaches to Advanced Information Technology

First International Workshop, BioADIT 2004, Lausanne, Switzerland, January 29-30, 2004. Revised Selected Papers

  • Conference proceedings
  • © 2004

Overview

Editors:
  1. Auke Jan Ijspeert

    1. Biologically Inspired Robotic Group (BIRG), Ecole Polytechnique Fédérale de Lausanne (EPFL), Station 14, Lausanne, Switzerland

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  2. Masayuki Murata

    1. Graduate School of Information Science and Technology, Osaka University, Suita, Osaka, Japan

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  3. Naoki Wakamiya

    1. Graduate School of Information Science and Technology, Osaka University, Suita, Osaka, Japan

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 3141)

Included in the following conference series:

Conference proceedings info: BioADIT 2004.

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Table of contents (36 papers)

  1. Front Matter

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  2. Biosystems for IT Evolution

    1. Object-Oriented Specification of Complex Bio-computing Processes: A Case Study of a Network of Proteolytic Enzymes

      • Jacqueline Signorini, Patrick Greussay
      Pages 1-12

    2. Analysis of Responses of Complex Bionetworks to Changes in Environmental Conditions

      • Hiroshi Shimizu, Takashi Hirasawa, Keisuke Nagahisa, Suteaki Shioya
      Pages 13-27

    3. Experimental Molecular Evolution Showing Flexibility of Fitness Leading to Coexistence and Diversification in Biological System

      • Akiko Kashiwagi, Wataru Noumachi, Masato Katsuno, Mohammad T. Alam, Itaru Urabe, Tetsuya Yomo
      Pages 28-39

    4. Echo State Networks and Self-Prediction

      • Norbert M. Mayer, Matthew Browne
      Pages 40-48

    5. Learning Bayesian Networks by Lamarckian Genetic Algorithm and Its Application to Yeast Cell-Cycle Gene Network Reconstruction from Time-Series Microarray Data

      • Sun-Chong Wang, Sai-Ping Li
      Pages 49-62

    6. Towards Cortex Sized Attractor ANN

      • Christopher Johansson, Anders Lansner
      Pages 63-79

  3. Bio-inspired Software Systems

    1. Biologically Inspired Reinforcement Learning: Reward-Based Decomposition for Multi-goal Environments

      • Weidong Zhou, Richard Coggins
      Pages 80-94

    2. Dynamic Self-Assembly and Computation: From Biological to Information Systems

      • Ann M. Bouchard, Gordon C. Osbourn
      Pages 95-110

    3. Implementation and Evaluation of a System to Support Human Relationship Formation in Networked Virtual Space

      • Yoshiharu Yoshimoto, Yuichi Itoh, Yoshifumi Kitamura, Fumio Kishino
      Pages 111-126

    4. Biologically Plausible Speech Recognition with LSTM Neural Nets

      • Alex Graves, Douglas Eck, Nicole Beringer, Juergen Schmidhuber
      Pages 127-136

    5. Spatial Tangible User Interfaces for Cognitive Assessment and Training

      • Ehud Sharlin, Yuichi Itoh, Benjamin Watson, Yoshifumi Kitamura, Steve Sutphen, Lili Liu et al.
      Pages 137-152

    6. Biologically Inspired Computer Virus Detection System

      • Hyungjoon Lee, Wonil Kim, Manpyo Hong
      Pages 153-165

    7. Explaining Low-Level Brightness-Contrast Illusions Using Disinhibition

      • Yingwei Yu, Takashi Yamauchi, Yoonsuck Choe
      Pages 166-175

    8. Autonomous Acquisition of the Meaning of Sensory States Through Sensory-Invariance Driven Action

      • Yoonsuck Choe, S. Kumar Bhamidipati
      Pages 176-188

  4. Hardware Systems

    1. Characterizing the Firing Properties of an Adaptive Analog VLSI Neuron

      • Daniel Ben Dayan Rubin, Elisabetta Chicca, Giacomo Indiveri
      Pages 189-200

    2. Embryonic Machines That Divide and Differentiate

      • Daniel Mange, André Stauffer, Enrico Petraglio, Gianluca Tempesti
      Pages 201-216

    3. Artificial Cellular Division by Self-Inspection

      • Enrico Petraglio, Daniel Mange, André Stauffer, Gianluca Tempesti
      Pages 217-232

    4. A Hardware Implementation of a Network of Functional Spiking Neurons with Hebbian Learning

      • Andrés Upegui, Carlos Andrés Peña-Reyes, Eduardo Sánchez
      Pages 233-243
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About this book

The evolution of the Internet has led us to the new era of the information infrastructure. As the information systems operating on the Internet are getting larger and more complicated, it is clear that the traditional approaches based on centralized mechanisms are no longer meaningful. One typical example can be found in the recent growing interest in a P2P (peer-to-peer) computing paradigm. It is quite different from the Web-based client-server systems, which adopt essentially centralized management mechanisms. The P2P computing environment has the potential to overcome bottlenecks in Web computing paradigm, but it introduces another difficulty, a scalability problem in terms of information found, if we use a brute-force flooding mechanism. As such, conventional information systems have been designed in a centralized fashion. As the Internet is deployed on a world scale, however, the information systems have been growing, and it becomes more and more difficult to ensure fau- free operation. This has long been a fundamental research topic in the field. A complex information system is becoming more than we can manage. For these reasons, there has recently been a significant increase in interest in biologically inspired approaches to designing future information systems that can be managed efficiently and correctly.

Editors and Affiliations

  • Biologically Inspired Robotic Group (BIRG), Ecole Polytechnique Fédérale de Lausanne (EPFL), Station 14, Lausanne, Switzerland

    Auke Jan Ijspeert

  • Graduate School of Information Science and Technology, Osaka University, Suita, Osaka, Japan

    Masayuki Murata, Naoki Wakamiya

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