Dr David Rajaratnam
Adjunct Lecturer

Dr David Rajaratnam

Computer Science and Engineering

I am a researcher in Artificial Intelligence (AI) and Robotics and an Adjunct Lecturer in the School of Computer Science and Engineering (CSE)

My research interests are in the areas of classical AI: knowledge representation, non-monotonic and commonsense reasoning, planning, cognitive robotics, general game playing and multi-agent systems.

I am particularly interested in the application of Answer Set Programming (ASP) as a technology for solving knowledge driven combinatorial problems. ASP is a knowledge representation and reasoning paradigm that has emerged over the last decade and provides a powerful tool for solving many classical AI problems; from scheduling and planning through to resource allocation problems. It can also be applied to more novel AI application such as ensuring consistency for automated document creation. ASP has a concise and transparent language for capturing knowledge with rich features for expressing both qualitative and quantitative optimisation constraints.

I also work in robotics, with a particular focus on cognitive robotics; which is the challenge of making a robot reason and behave intelligently. I am interested in the integration of different types of reasoning systems within a cognitive robotic system. For example, how do we connect a logical reasoner for planning high-level robot actions with the robot’s vision and object recognition system. Such a tight-integration can lead to more effective behaviour. For example, the planning system can bias the robot’s vision system in order to improve the detection of objects that the robot is expecting to encounter in its environment.

+61 2 9385 6533
  • Journal articles | 2019
    Rezvani M; Rajaratnam D; Ignjatovic A; Pagnucco M; Jha S, 2019, 'Analyzing XACML policies using answer set programming', International Journal of Information Security, vol. 18, pp. 465 - 479, http://dx.doi.org/10.1007/s10207-018-0421-5