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
Computational Intelligence for Complex Structured Data. This project aims to use computational intelligence techniques to reliably learn adaptive natural human pointing and gestures to control an interface on a pseudo-3D display. Highly complex data with interconnections between elements is hard to visualise on screens. Most current tools are operated using point/click/drag on 2D screens. The physical technology to capture appropriate human behaviours exists already, but not the adaptive learnin ....Computational Intelligence for Complex Structured Data. This project aims to use computational intelligence techniques to reliably learn adaptive natural human pointing and gestures to control an interface on a pseudo-3D display. Highly complex data with interconnections between elements is hard to visualise on screens. Most current tools are operated using point/click/drag on 2D screens. The physical technology to capture appropriate human behaviours exists already, but not the adaptive learning of the syntax and semantics of individual gestures and actions, nor the multi-gesture information fusion required for understanding, which could significantly enhance efficiency, for example, in sorting through named entities in an investigation. All of this is done naturally by most human beings, using biological neural networks.Read moreRead less
Probabilistic modeling of human responses in complex interaction. The project aims to develop computational ability to reliably detect and hence act on implicit user preferences. It aims to develop techniques combining advanced non-intrusive sensor measures of conscious and non-conscious behaviour during interaction tasks to enable very high-level computerised support for human goal-seeking in complex data and design environments. It plans to use a user’s physiology and preference evaluation to ....Probabilistic modeling of human responses in complex interaction. The project aims to develop computational ability to reliably detect and hence act on implicit user preferences. It aims to develop techniques combining advanced non-intrusive sensor measures of conscious and non-conscious behaviour during interaction tasks to enable very high-level computerised support for human goal-seeking in complex data and design environments. It plans to use a user’s physiology and preference evaluation to capture their complex interaction with the data they view, probability models to accumulate information to identify their underlying preferences and extract relationships to find possible ‘hidden variables’ which may help explain and leverage the user's choices.Read moreRead less
Cognitive intelligent information processing and presentation in navigation. This project aims to develop a personalised navigation system to provide effective augmented-reality (AR)-based support information, built on different navigation preference and the momentary cognitive workload of the user. This will immediately encourage users to become aware of their surroundings and continuous use will facilitate the development of navigation skills. It is expected that this research will advance sci ....Cognitive intelligent information processing and presentation in navigation. This project aims to develop a personalised navigation system to provide effective augmented-reality (AR)-based support information, built on different navigation preference and the momentary cognitive workload of the user. This will immediately encourage users to become aware of their surroundings and continuous use will facilitate the development of navigation skills. It is expected that this research will advance scientific knowledge about individual differences in navigation ability. It will significantly enhance spatial learning and alleviate the apparent decline in navigational ability experienced across the life span, benefiting the aged population in Australia by enabling them to live longer independent lives.Read moreRead less
An integrated and real-time passenger travel and public transport service information system. This project will help the Department of Transport provide improved services to the public through a better understanding of journey planning demands in comparison to public transport services. By integrating research through design methods with technological solutions, the project will deliver better quality of service and higher customer satisfaction.
AI-Human Empowered Team Decision-Making. This project aims to introduce machine intelligence into human team decision-making using the brain-to-brain synchrony that arises when people cooperate toward achieving a goal. The expected outcomes are models and indicators of this synchrony, and methods to fuse individual human decisions with autonomous machine agents, into collective decisions. This new knowledge is expected to greatly increase our understanding of cooperative decision-making by human ....AI-Human Empowered Team Decision-Making. This project aims to introduce machine intelligence into human team decision-making using the brain-to-brain synchrony that arises when people cooperate toward achieving a goal. The expected outcomes are models and indicators of this synchrony, and methods to fuse individual human decisions with autonomous machine agents, into collective decisions. This new knowledge is expected to greatly increase our understanding of cooperative decision-making by humans and machine agents. The tools produced are expected to provide a computational basis for human-autonomy teaming, the core of Industry 5.0, that software developers and end-users in various industries could further build upon to optimise complex decision-making to benefit humanity.Read moreRead less
Adaptive modelling of human responses in complex interaction. This project aims to combine strengths of human cognition and evolutionary computing to efficiently solve problems which neither can do alone. The project will develop techniques combining advanced non-intrusive sensor measures of behaviour and emotional reaction in interaction tasks to enable high level computer support for human goal seeking, in complex data and design environments. This project will allow non-expert users to use to ....Adaptive modelling of human responses in complex interaction. This project aims to combine strengths of human cognition and evolutionary computing to efficiently solve problems which neither can do alone. The project will develop techniques combining advanced non-intrusive sensor measures of behaviour and emotional reaction in interaction tasks to enable high level computer support for human goal seeking, in complex data and design environments. This project will allow non-expert users to use tools normally requiring extensive training in settings where the user can 'see' when they get something they like but do not know how to instruct a computer system to show or do it. Applications of the project will include visualisation for bespoke manufacturing or for high dimensional data, generating abstract art, or improving teleconferencing systems.Read moreRead less
Improvisational interfaces: developing new human-computer creativity. This project intends to introduce new methods for the design and use of creative software for both learning and professional artistic practice. Using innovative interactive techniques based on improvisation, the project seeks to significantly boost human creativity through improvisational dialogues of increasing sophistication between artists and computers. The project is designed to help create the next generation of digital ....Improvisational interfaces: developing new human-computer creativity. This project intends to introduce new methods for the design and use of creative software for both learning and professional artistic practice. Using innovative interactive techniques based on improvisation, the project seeks to significantly boost human creativity through improvisational dialogues of increasing sophistication between artists and computers. The project is designed to help create the next generation of digital arts software systems that will assist creative professionals in developing their own unique creative styles and encourage young people to develop their creative potential. These advancements would promote higher productivity and greater creativity vital to Australia's future creative industries.Read moreRead less
Brain Robot Interface for Physical Human Robot Collaboration. This project aims to discover new knowledge of cognitive conflict and develop models and algorithms that enable intuitive physical human-robot collaboration to jointly conduct laborious tasks in complex, unstructured environments. It proposes to build on responses in the human brain when a robot does not operate in a way the human expects. Conflict models and prediction method are planned using advanced machine learning algorithms. Th ....Brain Robot Interface for Physical Human Robot Collaboration. This project aims to discover new knowledge of cognitive conflict and develop models and algorithms that enable intuitive physical human-robot collaboration to jointly conduct laborious tasks in complex, unstructured environments. It proposes to build on responses in the human brain when a robot does not operate in a way the human expects. Conflict models and prediction method are planned using advanced machine learning algorithms. The model and algorithms are intended to be integrated into an innovative brain-robot interface for field testing in a real-world industrial task. Translation of the outcomes to industry is expected to produce substantial economic and societal benefits through improved productivity and safety.Read moreRead less
A neural fuzzy fusion engine for human-machine autonomous systems. This project aims to develop an intelligent engine to adaptively fuse multiple trust-based information from various agents in human machine autonomous systems (HMAS). The project will develop new techniques to detect covert-state drift, model trustworthiness between humans and machines, and adaptively fuse information under various kinds of uncertainty and trust levels. These techniques will be integrated to produce a general fra ....A neural fuzzy fusion engine for human-machine autonomous systems. This project aims to develop an intelligent engine to adaptively fuse multiple trust-based information from various agents in human machine autonomous systems (HMAS). The project will develop new techniques to detect covert-state drift, model trustworthiness between humans and machines, and adaptively fuse information under various kinds of uncertainty and trust levels. These techniques will be integrated to produce a general framework to facilitate human-machine interaction and enable better collaborative decisions in HMAS. The outcomes will benefit human-centric automation systems in general and next-generation autonomous vehicles in particular, which will contribute to the Australian economy.Read moreRead less