A Layered Controlled Natural Language for Knowledge Representation. In this research project we will develop a controlled natural language for knowledge representation that has the potential to bridge the gap between fragments of natural language and formal languages. This controlled language will be based on a variety of increasing sophisticated layers, each building upon those below it by providing enhancements in expressive power. Sentences of the controlled language will be unambiguously tra ....A Layered Controlled Natural Language for Knowledge Representation. In this research project we will develop a controlled natural language for knowledge representation that has the potential to bridge the gap between fragments of natural language and formal languages. This controlled language will be based on a variety of increasing sophisticated layers, each building upon those below it by providing enhancements in expressive power. Sentences of the controlled language will be unambiguously translatable into a corresponding formal language. Anyone who can read and write English can immediately use the controlled language with the help an intelligent text editor. This technology will make it possible for non-specialists to write problem specifications in terms of the application domain without the need to formally encode the information.Read moreRead less
Visualisation of large, complex networks through small, beautiful diagrams. Data is increasingly organised as networks. Visualisation is a key way to understand networks. This project plans to develop a new paradigm for this task. Using modern generic constrained optimisation techniques it will produce layouts for small graphs whose quality is similar to that produced by hand, something that is not possible with current approaches. These algorithms will then be used to visualise large graphs. In ....Visualisation of large, complex networks through small, beautiful diagrams. Data is increasingly organised as networks. Visualisation is a key way to understand networks. This project plans to develop a new paradigm for this task. Using modern generic constrained optimisation techniques it will produce layouts for small graphs whose quality is similar to that produced by hand, something that is not possible with current approaches. These algorithms will then be used to visualise large graphs. Instead of simply trying to visualise every node and link in the graph. The project will develop techniques to extract useful subsets or abstractions that are as small possible, yet sufficient to answer targeted queries. The techniques for producing small high-quality diagrams will then be applicable to presenting these focused visualisations.Read moreRead less
Special Research Initiatives - Grant ID: SR0567196
Funder
Australian Research Council
Funding Amount
$55,000.00
Summary
Improved early detection of breast cancer enabled by grid-computing and advanced modelling and visualisation of MR images. This project will investigate the utility of grid computing in the detection of breast cancer from magnetic resonance (MR) images. The large quantity of data acquired using MR imaging is difficult for clinicians to review and the cost of missed or incorrect detection is high. To provide rapid visualisation and assessment of the acquired data, grid computing will be used in c ....Improved early detection of breast cancer enabled by grid-computing and advanced modelling and visualisation of MR images. This project will investigate the utility of grid computing in the detection of breast cancer from magnetic resonance (MR) images. The large quantity of data acquired using MR imaging is difficult for clinicians to review and the cost of missed or incorrect detection is high. To provide rapid visualisation and assessment of the acquired data, grid computing will be used in conjunction with interactive visualisation with haptic feedback. Grid computing experience and haptic device expertise will be achieved via Swedish collaborators. The successful outcome of this project will be software for the production of 3D colour-coded breast images in which suspicious regions are highlighted and can be physically interrogated using the haptic device.Read moreRead less
Filters reveal what flicker conceals: temporal processing in the human visual system. I have recently discovered a new form of camouflage using 10Hz luminance flicker. This project will quantify this effect and examine the extent to which it generalises across colour and spatial dimensions and to video sequences depicting natural scenes. This information is expected to provide foundational information to technologies relating to national security that rely on visual concealment. This research wi ....Filters reveal what flicker conceals: temporal processing in the human visual system. I have recently discovered a new form of camouflage using 10Hz luminance flicker. This project will quantify this effect and examine the extent to which it generalises across colour and spatial dimensions and to video sequences depicting natural scenes. This information is expected to provide foundational information to technologies relating to national security that rely on visual concealment. This research will examine the extent to which filtering out these camouflaging frequencies enhances our sensitivity to low temporal frequency information. This decamouflaging aspect of my research is expected to improve the clarity of digital video-based technologies including ultrasound, educational, info-tainment and defence applicationsRead moreRead less
Explainable Artificial Creativity. This project aims to develop explainable models for creative AI systems which enable more productive and satisfying interactions between them and their human co-creators. This will boost both human and machine creativity through sustained, ongoing exchanges, leading to high-quality creative outcomes via automated ideation and more advanced human-machine collaborations. The proposed techniques will be validated with creative professionals, ensuring practical ind ....Explainable Artificial Creativity. This project aims to develop explainable models for creative AI systems which enable more productive and satisfying interactions between them and their human co-creators. This will boost both human and machine creativity through sustained, ongoing exchanges, leading to high-quality creative outcomes via automated ideation and more advanced human-machine collaborations. The proposed techniques will be validated with creative professionals, ensuring practical industry relevance. We expect the outcomes to include new methods that automatically generate persuasive explanations, new forms of communication including dialogues between creative AI systems and users, and new understanding of general aspects of explainability for creative AI systems.Read moreRead less
Autonomous Functions for Smart Cars. The aim of this project is to develop autonomous functions for smart cars, such as lane departure warning, driver fatigue warning, and automatic lane following. Every year 70,000 people are killed in road accidents, 95% of which can be attributed to driver error. The potential outcomes of this project therefore significant. Many of the theoretical methods required for this project have been developed by our group. However, further theoretical refinements fo ....Autonomous Functions for Smart Cars. The aim of this project is to develop autonomous functions for smart cars, such as lane departure warning, driver fatigue warning, and automatic lane following. Every year 70,000 people are killed in road accidents, 95% of which can be attributed to driver error. The potential outcomes of this project therefore significant. Many of the theoretical methods required for this project have been developed by our group. However, further theoretical refinements followed by experimental verification is necessary. For smart cars to be accepted, the systems must be demonstrated to be reliable and to operate in a wide range of conditions.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE220100265
Funder
Australian Research Council
Funding Amount
$417,000.00
Summary
A closed-loop human–agent learning framework to enhance decision making. This project aims to design a foundational human–agent learning framework to augment the decision making process, using reinforcement and closed-loop mechanisms to enable symbiosis between a human and an artificial-intelligence agent. It envisages significant new technologies to promote controllability and efficient and safe exploration of an environment for decision actions – drastically boosting learning effectiveness and ....A closed-loop human–agent learning framework to enhance decision making. This project aims to design a foundational human–agent learning framework to augment the decision making process, using reinforcement and closed-loop mechanisms to enable symbiosis between a human and an artificial-intelligence agent. It envisages significant new technologies to promote controllability and efficient and safe exploration of an environment for decision actions – drastically boosting learning effectiveness and interpretability in decision making. Expected outcomes will benefit national cybersecurity by improving our understanding of vulnerabilities and threats involving decision actions, and by ensuring that human feedback and evaluations can help prevent catastrophic events in explorations of dynamic and complex environments.Read moreRead less
Operator Decision Modelling in Autonomous Systems. The incorporation of humans as decision-makers into a complex system comprising of many autonomous agents is becoming increasingly important in areas such as defence, search-and-rescue, special emergency services, bush-fire and ecology management. This project will address how human decisions are made in such systems through the formulation and demonstration of innovative algorithms which model the operator decision making process. Generating so ....Operator Decision Modelling in Autonomous Systems. The incorporation of humans as decision-makers into a complex system comprising of many autonomous agents is becoming increasingly important in areas such as defence, search-and-rescue, special emergency services, bush-fire and ecology management. This project will address how human decisions are made in such systems through the formulation and demonstration of innovative algorithms which model the operator decision making process. Generating solutions to this increasingly important area will provide Australia's industry and community services the necessary knowledge for deploying such systems and thus improving service effectiveness, as well as the implementation of autonomous systems into new areas and thus increasing economic growth.Read moreRead less
Development of a three dimensional audio-visual next generation speech recognition system. To overcome the disadvantages of current Audio-Visual Speech Recognition Systems, we propose a set of robust algorithms in three dimensional computer vision and speech processing. The proposed system will have far-reaching implications in various areas, for example, human-machine interaction for speech recognition in automated dialog systems and voice-to-text conversions.
A computational theory of strategic deception. This artificial project aims to develop a theory of strategic deception and test it through an Artificial Intelligence model. The project will combine computational Theory-of-Mind concepts with recent scientific findings to allow us to better understand whether and how intelligent technologies of the future might deceive humans. The findings will provide new insights into how Artificial Intelligence technologies of the future will impact applied are ....A computational theory of strategic deception. This artificial project aims to develop a theory of strategic deception and test it through an Artificial Intelligence model. The project will combine computational Theory-of-Mind concepts with recent scientific findings to allow us to better understand whether and how intelligent technologies of the future might deceive humans. The findings will provide new insights into how Artificial Intelligence technologies of the future will impact applied areas of computing, where simulating advanced forms of social behaviour and cognition, including deception, will become increasingly significant.Read moreRead less