Smart quality management for service-based systems in cloud environment. Cloud computing is a rapidly growing paradigm for Software-as-a-Service (SaaS). For enabling broad applications of a huge number of services available in the cloud, quality management for service-based systems is critical. This project aims to cover smart quality management for the whole lifetime of SaaS from service composition to service delivery. The project is expected to offer a novel solution for managing both build-t ....Smart quality management for service-based systems in cloud environment. Cloud computing is a rapidly growing paradigm for Software-as-a-Service (SaaS). For enabling broad applications of a huge number of services available in the cloud, quality management for service-based systems is critical. This project aims to cover smart quality management for the whole lifetime of SaaS from service composition to service delivery. The project is expected to offer a novel solution for managing both build-time service selection and runtime service monitoring and adaptation by inventing corresponding innovative efficient and effective strategies for quality management. Given the prediction that the SaaS market will grow from $13.5 billion in 2011 to $32.8 billion in 2016, the success of this project is anticipated to translate into scientific and economic value.Read moreRead less
Optimisation of embedded virtual complex systems by re-using a library of available components. Nowadays, there are benefits in building complex embedded systems, such as a house surveillance agent, by re-using and combining available modules, such as cameras, blinds, phones, lights, etc. Because complete construction may be impossible, this project devises methods for automatically achieving the desired system to the highest-degree possible.
Representation and Reasoning for Cognitive Personal Robotics. Robotic systems are becoming increasingly more sophisticated and prevalent. Developing complex and maintainable robot programs to control these systems remains a significant challenge particularly given the diversity of robot platforms and application areas. This project aims to build on advances in problem solving and programming paradigms in Artificial Intelligence, applying them to learning sophisticated robot programs. These techn ....Representation and Reasoning for Cognitive Personal Robotics. Robotic systems are becoming increasingly more sophisticated and prevalent. Developing complex and maintainable robot programs to control these systems remains a significant challenge particularly given the diversity of robot platforms and application areas. This project aims to build on advances in problem solving and programming paradigms in Artificial Intelligence, applying them to learning sophisticated robot programs. These techniques have the potential to provide for elaboration tolerance, knowledge/program maintenance and optimisation of performance. This project aims to develop techniques for building sophisticated declarative robot programs. It aims to achieve this by learning procedural robot programs and turning them into maintainable declarative robot programs.Read moreRead less
Representing and reasoning about ability for robots to use the cloud. While robots have come a long way they are still hampered by processing and data storage limitations. Component based robot middleware and facilities provided by cloud computing provide means for addressing these issues. This project develops technology for representing and reasoning about robot abilities so as to take advantage of these advances.
Making the Pilbara blend: agile mine scheduling through contingent planning. Mine scheduling is a challenging problem for Rio Tinto which annually mines more than 200 Million tonnes of iron ore. This project will develop agile scheduling techniques of great economic importance to Australia. Carefully planned scheduling reduces infrastructure and minimises environmental impacts, maximising regeneration after mining.
Context-aware verification and validation framework for autonomous driving. This project aims to enhance the reliability and safety of emerging self-driving vehicles, through a framework that supports the validation and verification of autonomous driving systems. This project expects to generate new knowledge in areas of software engineering, intelligent transport, and machine learning, using a multi-disciplinary research combining expertise from various fields. Expected outcomes of this project ....Context-aware verification and validation framework for autonomous driving. This project aims to enhance the reliability and safety of emerging self-driving vehicles, through a framework that supports the validation and verification of autonomous driving systems. This project expects to generate new knowledge in areas of software engineering, intelligent transport, and machine learning, using a multi-disciplinary research combining expertise from various fields. Expected outcomes of this project are a family of new context-aware techniques to verify and validate complex behaviours in autonomous driving. This should provide significant benefits, such as safe autonomous driving systems and the improved journey experience and security for road users.Read moreRead less