CIRG | News

By: Cirg  11-11-2011
Keywords: Neural Networks, Swarm Intelligence, Intelligence Research

LATEST NEWS

Postdoctoral Fellowships Available:

The Computational Intelligence Research Group has a number of postdoctoral and research fellowships available. These followships are for research in

  • Computational Swarm Intelligence, with a specific focus on development of swarm-based algorithms to solve complex optimization problems, e.g. finding multiple solutions, tracking solutions in dynamic environments, dynamic multi-objectibe optimization, dynamic constraints, amongst others
  • Swarm robotics, with a focus on the development of self-organization models to control robot swarms
  • Competitive and co-evolutionary systems, with a focus on evolving neur-controllers, neural networks training, and optimization
  • Neural networks, with a focus on training algorithms, architecture optimization, and active learning strategies in dynamic environments

To qualify for these fellowships, you have to:

  • be 40 years of age or younger
  • have obtained your PhD within the last 5 years
  • have a proven research record in areas of computational intelligence

In considering these fellowships, please note the difference between the two:

  • Postdoctoral fellowships are awarded for a period of 1 to 2 years, and consists of a tax-free grant to conduct research in one of the above areas
  • Research fellow ships are awarded for a period of 2 to 5 years, and are appointed on a contract basis. Fellows are expected to do research in one of the areas above and to help with postgraduate student supervision.

31 January 2011

CIRG has been very successful in its submissions to several symposia of the IEEE Symposium Series on Computational Intelligence (IEEE SSCI). The following articles have been accepted for submission at the IEEE SSCI in Paris during the second week of April:

  • AP Engelbrecht, Scalability of A Heterogeneous Particle Swarm Optimizer, accepted for IEEE Swarm Intelligence Symposium
  • JF Nicholls, KM Malan, AP Engelbrecht, Comparison of Trade Decision Strategies in an Equity Market GA Trader, accepted for IEEE Symposium on Computational Intelligence for Financial Engineering & Economics
  • E Papacostantics, AP Engelbrecht, Coevolutionary Particle Swarm Optimization for Evolving Trend Reversal Indicators, accepted for IEEE Symposium on Computational Intelligence for Financial Engineering & Economics
  • G Pampara, AP Engelbrecht, Binary Artificial Bee Colony Optimization, accepted for IEEE Swarm Intelligence Symposium
  • BJ Leonard, AP Engelbrecht, AB van Wyk, Heterogeneous Particle Swarms in Dynamic Environments, accepted for IEEE Swarm Intelligence Symposium
  • AB van Wyk, AP Engelbrecht, Lamda-Gamma Learning with Feedforward Neural Networks using Particle Swarm Optimization, accepted for IEEE Swarm Intelligence Symposium
  • MC du Plessis, AP Engelbrecht, Self-Adaptive Competitive Differential Evolution for Dynamic Environments, accepted for Symposium on Differential Evolution
  • R Klazar, AP Engelbrecht, Dynamic Load Balancing Inspired by Division of Labour in Ant Colonies, accepted for IEEE Swarm Intelligence Symposium

Latest

Recently, the following journal articles have been published:

  • W Matthysen, AP Engelbrecht, A Polar Coordinate Particle Swarm Optimiser, Applied Soft Computing, 11(1):1322--1339, 2011
  • AJ Graaff, AP Engelbrecht, Clustering Data in an Uncertain Environment using an Artificial Immune System, Pattern Recognition Letters, 32(2):342—351, 2011
  • AJ Graaff, AP Engelbrecht, Using Sequential Deviation to Dynamically Determine the Number of Clusters Found by a Local Network Neighbourhood Artificial Immune System, Applied Soft Computing, 11:2698--2713, 2011

Keywords: Intelligence Research, Neural Networks, Particle Swarm Optimization, Swarm Intelligence,