School of Engineering and Information Technology

Topics studied by the Developmental Systems and Machine Learning group lie at the intersection of cognitive science, developmental robotics, virtual worlds and machine learning research. Cognitive science is the interdisciplinary study of how information used during perception, language, reasoning, motivation and emotion, is represented and processed, either in a human or animal, or by a machine (specifically a computer in our case). Developmental robotics and character animation in virtual worlds are application areas that use principles of cognitive and developmental sciences to build artificial systems capable of ontogenetic development. Such systems initially have little or no domain-specific knowledge or skills in their “infant” stage, but are equipped with generic reasoning mechanisms that permit them to acquire such knowledge and skills through interaction with their environment as they mature to an “adult” stage.

Researcher areas of interest to the Developmental Systems and Machine Learning group include, but are not limited to, reinforcement learning, neural networks, data mining, ensemble learning and learning classifier systems, as well as naturally inspired cognitive models, genetic and evolutionary systems. Applications include robotics, digital characters in virtual worlds, intelligent environments, network intrusion detection and social networks.

Highlights in 2011 include the renovation of the Developmental Robotics Laboratory, commencement of a fortnightly research meeting in conjunction with the Virtual Environments and Simulation Laboratory and the welcoming of two new postgraduate students.