Research Projects

Security & Trust in Multi-Agent Systems

Multi-agent systems (MAS) consist of a collection of agents (software programs) that interact with each other in dynamic, unpredictable environments. A fundamental question in MAS is whether messages, sent and received by agents, have been regarded as trustworthy. Therefore, it is important to provide a formal method for specifying trust that agents place in the security mechanisms of the system, so as to support reasoning about its security properties. Various formalisms have been proposed for specifying trust mechanisms in MAS. Most of them only deal with the static aspects of trust and ignore the evolution of trust relationships over time. This project is developing a novel formalism for specifying dynamic trust relationships as the agents in MAS gain or lose confidence in the agents and the environment in which they operate. Certain aspects of this project has been funded by MURDG's and a multi-campus ARC Discovery Project (2005-2007) held at the University of Western Sydney.

Formal Approaches to Intelligent Systems

Logical representations have been widely used in Computer Science and Artificial Intelligence (AI). However, as the problems tackled have become more complex, the requirement for more powerful logical representations has been growing. In particular, since the concept of time is of central importance to an increasingly wide range of applications, including the representation of time-dependent data, modeling reactive systems, and the specification and verification of concurrent and distributed systems, many logics incorporating temporal notions are being developed and applied. Then the development of executable temporal logics followed so that system developers have access to these, more powerful, logical techniques. We have proposed and investigated one of the earliest executable temporal logic systems called Chronolog (for Chronological logic programming). Chronolog is a language in which one can specify dynamic systems whose behaviour varies with time. We have also investigated extensions of Chronolog where one can specify and reason about the time-dependent properties of reactive, multi-agent systems where components (and agents) run on different clocks with varying rates of progress. Dr. C. Liu from DSTO (Edinburgh) and Prof. W. Wadge from University of Victoria (Canada) have been involved in the theoretical aspects of the project. The implementation work on Chronolog has been carried out jointly with Prof. K. Zhang of University of Texas, Dallas. Aspects of this project has been funded by MURGs, small ARC grants, one ARC Discovery Project under Innovation Initiative(2002), and currently by a 5-year, multi-campus ARC Discovery Project (2004-2008) held at Griffith University, involving five investigators from five different institutions.

Temporal Models and Algebras for Databases

The ability to model the temporal dimension of real world is essential to many computer system applications, such as banking, inventory control, student records, and airline reservations. Yet conventional database systems do not adequately support the time-varying aspect of the real-world phenomena. This project was concerned with the investigation of the fundamental problems in representing and querying time-varying information with the relational database technology, and providing application-independent solutions to those problems. The focus was on incorporating an implicit time dimension into the relational model and algebra, through the use of temporal logic. The resulting temporal algebra can be used as a testbed for the further study and exploration of the important properties such as completeness and the expressive capabilities that temporal query languages should exhibit. We also showed that a representation-independent temporal data model based on temporal logic makes possible the study of integration and interoperability of different, and representation-dependent temporal data models within a single, precise framework. This project was mainly funded by a large ARC grant (1996-1998).

Modelling and Reasoning about Multidimensional Information

In many computer applications, multidimensional information is pervasive, for example, time series, forex data, spatial information, weather forecast data and so on. Multidimensional nature of such applications also demands more sophisticated techniques and tools for the representation and manipulation of multidimensional information. Most of the approaches proposed so far have been application-dependent, they do not have a clear and well-defined underlying formalism, and hence they do not easily generalise to other application domains. These shortcomings restrict their wide acceptance and use. We demonstrated that the use of executable multidimensional logics enhanced with aggregation operators in support of OLAP functionalities can remedy some of the shortcomings of the existing approaches. I have collaborated with Dr. R. Wong of UNSW/NICTA and A/Prof. W. Du of The University of New Brunswick (Canada) in this project which was mainly funded by MURGs and a large ARC grant (2000-2002).

Temporal Data Mining

In many business applications, a great deal of temporal data has been stored in corporate data warehouses. Examples range from transaction databases in health care and insurance, patient records, and stock exchange, to scientific databases in geophysics and astronomy. The growth of research and applications on temporal databases and data warehouses has motivated an urgent need for techniques to deal with the problem of knowledge discovery from large temporal databases. This project is concerned with the investigation of a model for temporal support in data mining and associated techniques and methods. This project has been funded by MURGs, an ongoing ARC Linkage grant with the Australian Taxation Office (ATO) as the industry partner, and more recently Capital Markets CRC project seed funding.

Software reverse engineering

This project was concerned with the development of tools and techniques for reverse engineering and software analysis. Reverse engineering is the process of extracting system abstractions and design information out of existing software systems for maintenance and re-engineering purposes. This process involves the identification of software artifacts in a subject system, the exploration of the way in which these artifacts interact with one another, and the aggregation of the artifacts to form more abstract system representations that facilitate program understanding. Of particular interest was the Rigi approach to reverse engineering based on module interconnection models and subsystem hierarchies identified by interactive, semi-automatic reconstruction of system representations. This was a joint project with Prof. Hausi Muller of the University of Victoria (Canada), primarily funded by MURGs.