Biologically Inspired Approaches to Advanced Information Technology

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

5. Robotics

   1. A Study on Designing Robot Controllers by Using Reinforcement Learning with Evolutionary State Recruitment Strategy

      • Toshiyuki Kondo, Koji Ito

      Pages 244-257

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.

• Bayesian network
• algorithmic learning
• algorithms
• ant algorithms
• artificial immune sys
• biocomputing
• bioinspired computing
• biologically motivated computing
• image processing
• information system
• intelligence
• natural computing
• robotics
• self-organization
• speech recognition
• algorithm analysis and problem complexity

• 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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