School of Computer Science and Software Engineering

Artificial Intelligence

In the early days of computing it was often stated that computers could never exhibit “intelligence” because they could only carry out tasks that their programmers had anticipated and pre-programmed solutions for. 

Advances in areas such as Artificial Intelligence, Machine Learning, Evolutionary Computation, Neural Networks, Data Mining and Automated Reasoning have shown that computers are capable of far more. 

Current projects

  • Computational Intelligence Techniques for Optimisation, Modelling and Control
  • Applications of multi-objective evolutionary algorithms
  • Evolutionary optimisation and design
  • Hypervolume calculation for multi-objective optimisation
  • Evolutionary learning and games
  • Smart Home for Successful Aging Flexible Technologies for aging independently and knowledgeably
  • Agent and Web Services
  • Agent Autonomy for AIBO Entertainment Robot
  • Ontology Learning and Discovery using Corpus Analysis
  • Trust and Social Network Analysis.

Research groups

Adaptive System

The Adaptive System Research Group (ASRG) researches and develops computational systems that are able to adapt to or learn from the data, knowledge or environment in which they are working.  These systems typically mimic processes found in nature.  We seek to develop computational systems that employ evolutionary, learning, optimisation and modelling techniques to solve or improve performance on complex problems.

Walking Fish Group

Many problems faced by companies are impractical to solve by traditional analytical methods. Such problems may be computationally intractable, or may involve highly non-linear, complex systems. These difficulties offer no impediment to evolutionary algorithms. The Walking Fish Group focuses on such systems, their algorithms and the suitability of the proposed solutions. 

Multi-Agent Systems

As the name suggests, multi-agent systems are made up of multiple single agents.  This allows them to provide solutions to problems that are inherently too complex or impractical for single agent systems.

 

School of Computer Science and Software Engineering

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Last updated:
Tuesday, 5 November, 2013 11:25 AM

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