2014 IEEE Symposium on

Computational Intelligence in

Dynamic and Uncertain Environments


December 9-12, 2014, Orlando, Florida, USA

IEEE CIDUE'2014 will be held simultaneously with over 20 other symposia and workshops in one location at the IEEE Symposium Series on Computational Intelligence 2014 (IEEE SSCI 2014). This international event promotes all aspects of the theory and applications of computational intelligence. Sponsored by the IEEE Computational Intelligence Society, this event will attract top researchers, professionals, practitioners and students from around the world. The registration to SSCI 2014 will allow participants to attend all the symposia, including the complete set of the proceedings of all the meetings, coffee breaks, lunches, and the banquet.


IEEE CIDUE'2014 aims to bring together all researchers, practitioners and students to present and discuss the latest advances in the field of Computational Intelligence (CI), such as neural networks and learning algorithms, fuzzy systems, evolutionary computation and other emerging techniques for dealing with uncertainties encountered in evolutionary optimization, machine learning and data mining. Topics of the interest include but are not limited to:

  • Evolutionary computation in dynamic and uncertain environments
    • Use of surrogates for single and multi-objective optimization
    • Search for robust solutions over space and time
    • Dynamic single and multi-objective optimization
    • Handling noisy fitness functions
    • Learning and adaptation in evolutionary computation
  • Learning in non-stationary and uncertain environments
    • Incremental and lifelong learning
    • Online and interactive learning
    • Dealing with catastrophic forgetting
    • Active and autonomous learning in changing environments
    • Ensemble techniques
    • Multi-objective learning
    • Learning from severely unbalanced data, including multiclass unbalanced data.
  • Mining of temporal patterns
    • Temporal data mining techniques and methodologies
    • Incorporating domain knowledge for efficient temporal data mining
    • Scalability of temporal data mining algorithms
    • Mining of temporal data on the web
  • Hybrid methodologies for dealing with uncertainties, interactions of evolution and learning in changing environments, benchmarks, performance measures, and real-world applications

Important Dates

Paper submissions due July 15, 2014
Notification to authors September 5, 2014
Camera-ready papers due October 5, 2014

Program Chairs

Michael Beer

Yaochu Jin

University of Surrey, UK

Vladik Kreinovich

Robi Polikar

Rowan University, USA


Rudolf Kruse

Shengxiang Yang

De Montfort University, UK





IEEE SSCI 2014 Symposia



Welcome to IEEE SSCI'14 in Orlando, Florida, December 9 to 12, 2014

Copyright © 2014 IEEE Symposium Series on Computational Intelligence