Welcome to the home page of the Intelligent Computing Research Group.

Mission Statement

• To conduct international quality research of a beneficial nature, developing and applying state of the art techniques in artificial intelligence, cognitive science, and allied disciplines.
• To collect together the expertise and resources needed to help students experience the excitement of research.
• To provide an access point for researchers, research groups and commercial organisations outside the Department to information about the Group's interests and activities.

Research Focus

The biological world has been remarkably successful at problem solving as a result of the processes of evolution, learning and cooperative behaviour. This applies from simple organisms right through to the higher cognitive functions of humans. The aim of the ICRG is to harness this success in the "artificial" world of computing. This includes the analysis and application of population-based search and optimisation techniques (evolutionary computation), the development of programming techniques inspired by human cognitive abilities (artificial intelligence) and the use of computational models to better understand cognitive structure and functioning (cognitive science).

Current Research Interests

Techniques

• Logics for Artificial Intelligence (Nonclassical Logics)
• Machine Learning
• Evolutionary Search and Optimisation
• Statistical Analysis of Search Strategies
• Object-oriented Programming and Specification

Applications

• Knowledge Acquisition and Representation
• Automated Reasoning
• Adaptive Planning
• Declarative Modelling
• Intelligent Tutoring and Assessment
• Games of Strategy
• Computational Nanotechnology
• Computational Linguistics
• Automated Code Verification against Specifications

Group Members

• Lecturers
  • Cara MacNish
  • Luigi Barone
• Research Students
  • Andrew Czarn
  • Daniel Midgley
• Honours Students
  • Ritchie Phillips

External Collaborators

Shelly Harrison, Centre for Linguistics, UWA.
Mike Kailish, Psychology, UWA.
Grigoris Antoniou, School of Computing and Information Technology, Griffith University.
Mary-Anne Williams, Information Systems Group, University of Newcastle.

Associated Groups

Robotics and Vision Group, UWA.
Logic and AI Laboratory, UWA.
Intelligent Information Systems, Australia.

On-line Resources

• Electronic copies of theses
  Listed alphabetically. The usual filename extensions apply (ps - postscript, gz - gzipped, etc)
• External AI Repositories and Bibliographies
• Online Journals
• UseNet (Newsgroups)
• Other Interesting Sites

Origins

Figures

1. Snapshop of software developed within the group for comparing the performance of different update strategies in iterative optimisers such as the particle swarm optimiser.
2. Illustration of a declarative model for predicting system behaviour using logical inference in a nonmonotonic temporal reasoning system (implemented in Prolog and C).
3. Photo of a nanoscale surface taken by Daniel with a scanning tunneling microscope (STM).