9. Learning Techniques for Context Diagnosis and Prediction in Cognitive Communications

  1. David Grace2 and
  2. Honggang Zhang3
  1. Aimilia Bantouna,
  2. Kostas Tsagkaris,
  3. Vera Stavroulaki,
  4. Giorgos Poulios and
  5. Panagiotis Demestichas

Published Online: 24 JUL 2012

DOI: 10.1002/9781118360316.ch9

Cognitive Communications: Distributed Artificial Intelligence (DAI), Regulatory Policy & Economics, Implementation

Cognitive Communications: Distributed Artificial Intelligence (DAI), Regulatory Policy & Economics, Implementation

How to Cite

Bantouna, A., Tsagkaris, K., Stavroulaki, V., Poulios, G. and Demestichas, P. (2012) Learning Techniques for Context Diagnosis and Prediction in Cognitive Communications, in Cognitive Communications: Distributed Artificial Intelligence (DAI), Regulatory Policy & Economics, Implementation (eds D. Grace and H. Zhang), John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9781118360316.ch9

Editor Information

  1. 2

    Department of Electronics, University of York, UK

  2. 3

    Department of Information Science and Electronic Engineering, Zhejiang University, China

Author Information

  1. Department of Digital Systems, Telecommunication Networks and Integrated Services (TNS) Laboratory, University of Piraeus, Piraeus, Greece

Publication History

  1. Published Online: 24 JUL 2012
  2. Published Print: 31 AUG 2012

ISBN Information

Print ISBN: 9781119951506

Online ISBN: 9781118360316

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Keywords:

  • learning techniques for context diagnosis/prediction in cognitive;
  • cognition, changing behaviour of devices and networks;
  • boosting resource utilization, cognitive communications and knowledge;
  • intelligent/qualitative decisions on resource usage/configuration;
  • knowledge-based, application to heterogeneous, wireless environments;
  • learning network capabilities, using Bayesian networks;
  • building knowledge of network capabilities, and SOM;
  • “Winning” test case, CTMS for learning, on user devices

Summary

This chapter contains sections titled:

  • Introduction

  • Prediction

  • Future Problems

  • Conclusions

  • References