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Artificial Intelligence XXXIV

37th SGAI International Conference on Artificial Intelligence, AI 2017, Cambridge, UK, December 12-14, 2017, Proceedings

  • Conference proceedings
  • © 2017

Overview

Editors:
  1. Max Bramer

    1. University of Portsmouth, Portsmouth, United Kingdom

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    You can also search for this editor in PubMed   Google Scholar

  2. Miltos Petridis

    1. Middlesex University , London, United Kingdom

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 10630)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: SGAI 2017.

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About this book

This book constitutes the proceedings of the 37th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, AI 2017, held in Cambridge, UK, in December 2017.

The 25 full papers and 12 short papers presented in this volume were carefully reviewed and selected from 55 submissions. There are technical and application papers which were organized in topical sections named: machine learning and neural networks; machine learning, speech and vision and fuzzy logic; short technical papers; AI for healthcare; applications of machine learning; applications of neural networks and fuzzy logic; case-based reasoning; AI techniques; and short applications papers. 

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Table of contents (37 papers)

  1. Front Matter

    Pages I-XIV
    Download chapter PDF

  2. Technical Stream Papers

    1. Front Matter

      Pages 1-2
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    2. Using Constraint Satisfaction Problem Solving to Enable Workflow Flexibility by Deviation (Best Technical Paper)

      • Lisa Grumbach, Ralph Bergmann
      Pages 3-17

  3. Machine Learning and Neural Networks

    1. Front Matter

      Pages 19-19
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    2. Masked Conditional Neural Networks for Environmental Sound Classification

      • Fady Medhat, David Chesmore, John Robinson
      Pages 21-33

    3. Ensembles of Recurrent Neural Networks for Robust Time Series Forecasting

      • Sascha Krstanovic, Heiko Paulheim
      Pages 34-46

    4. A Blackboard Based Hybrid Multi-Agent System for Improving Classification Accuracy Using Reinforcement Learning Techniques

      • Vasileios Manousakis Kokorakis, Miltos Petridis, Stelios Kapetanakis
      Pages 47-57

  4. Machine Learning, Speech and Vision and Fuzzy Logic

    1. Front Matter

      Pages 59-59
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    2. Programming Without Program or How to Program in Natural Language Utterances

      • Martin J. Wheatman
      Pages 61-71

    3. Capturing the Dynamics of Cellular Automata, for the Generation of Synthetic Persian Music, Using Conditional Restricted Boltzmann Machines

      • Sahar Arshi, Darryl N. Davis
      Pages 72-86

    4. Measuring Relations Between Concepts in Conceptual Spaces

      • Lucas Bechberger, Kai-Uwe Kühnberger
      Pages 87-100

    5. Towards a Deep Reinforcement Learning Approach for Tower Line Wars

      • Per-Arne Andersen, Morten Goodwin, Ole-Christoffer Granmo
      Pages 101-114

    6. Improving Modular Classification Rule Induction with G-Prism Using Dynamic Rule Term Boundaries

      • Manal Almutairi, Frederic Stahl, Max Bramer
      Pages 115-128

  5. Short Technical Papers

    1. Front Matter

      Pages 129-129
      Download chapter PDF

    2. Inference and Discovery in Remote Sensing Data with Features Extracted Using Deep Networks

      • Isabel Sargent, Jonathon Hare, David Young, Olivia Wilson, Charis Doidge, David Holland et al.
      Pages 131-136

    3. Quantization Error-Based Regularization in Neural Networks

      • Kazutoshi Hirose, Kota Ando, Kodai Ueyoshi, Masayuki Ikebe, Tetsuya Asai, Masato Motomura et al.
      Pages 137-142

    4. Knowledge Transfer in Neural Language Models

      • Peter John Hampton, Hui Wang, Zhiwei Lin
      Pages 143-148

    5. Emotion Recognition in Text Using PPM

      • Amer Almahdawi, William John Teahan
      Pages 149-155

    6. An Experimental Comparison of Ensemble Classifiers for Evolving Data Streams

      • Ahmad Idris Tambuwal, Daniel Neagu, Marian Gheorghe
      Pages 156-162

    7. A Learning Automata Local Contribution Sampling Applied to Hydropower Production Optimisation

      • Jahn Thomas Fidje, Christian KrÃ¥kevik Haraldseid, Ole-Christoffer Granmo, Morten Goodwin, Bernt Viggo Matheussen
      Pages 163-168
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Other volumes

  1. Artificial Intelligence XXXIV

Editors and Affiliations

  • University of Portsmouth, Portsmouth, United Kingdom

    Max Bramer

  • Middlesex University , London, United Kingdom

    Miltos Petridis

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