Unifying Foundations for Intelligent Agents. This project aims to drive forward the development of rigorous foundations for intelligent agents. The agent framework, the expected utility principle, sequential decision theory, and the information-theoretic foundations of inductive reasoning and machine learning have already brought significant order into the previously heterogeneous scattered field of artificial intelligence. This project aims to investigate an information-theoretic approach towar ....Unifying Foundations for Intelligent Agents. This project aims to drive forward the development of rigorous foundations for intelligent agents. The agent framework, the expected utility principle, sequential decision theory, and the information-theoretic foundations of inductive reasoning and machine learning have already brought significant order into the previously heterogeneous scattered field of artificial intelligence. This project aims to investigate an information-theoretic approach towards a unifying foundation for intelligent agents, which has recently spawned impressive applications. The theory is expected to provide a gold standard and valuable guidance for researchers working on smart software.Read moreRead less
Feature reinforcement learning. Agent applications include speech recognition systems, vision systems, search engines, auto-pilots, spam filters, and robots. The research outputs from this project will enable agents to adapt to their environment and automatically, during deployment, acquire much of the knowledge that is currently required to be built in by agent designers.
On-line planning for constrained autonomous agents in an uncertain world. This project aims to develop admissible heuristics for constrained stochastic planning problems and integrate them into state-of-the-art on-line algorithms. Artificial Intelligence (AI) systems, such as self-driving cars or energy management systems, make intelligent decisions to act near-optimally in uncertain environments, leading to savings, for example in energy use. But we also want assurances that AI systems will obe ....On-line planning for constrained autonomous agents in an uncertain world. This project aims to develop admissible heuristics for constrained stochastic planning problems and integrate them into state-of-the-art on-line algorithms. Artificial Intelligence (AI) systems, such as self-driving cars or energy management systems, make intelligent decisions to act near-optimally in uncertain environments, leading to savings, for example in energy use. But we also want assurances that AI systems will obey safety constraints. Solving constrained stochastic planning problems is key to building AI that is both robust and safe. This project will explore ways to account for uncertainty and constraints in heuristic estimation.Read moreRead less
Lifelong robotic navigation using visual perception. Service robots are becoming a major part of our working and personal environments, in much the same way as personal computers already have. This project will develop new methods of practical and useful robot navigation that will enable Australia's industries and services to remain internationally competitive.
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE240100068
Funder
Australian Research Council
Funding Amount
$931,950.00
Summary
Australian Advanced Metabolic Signal Discovery, and Imaging Platform. This proposal aims to establish an Australian Advanced Metabolic Signal Discovery and Imaging platform. The platform consists of an ultra-high resolution gas chromatography mass spectrometer and an imaging mass spectrometry upgrade for a second existing high resolution mass spectrometer. The facility will break barriers currently limiting discovery and localisation of metabolic changes during plant and animal development under ....Australian Advanced Metabolic Signal Discovery, and Imaging Platform. This proposal aims to establish an Australian Advanced Metabolic Signal Discovery and Imaging platform. The platform consists of an ultra-high resolution gas chromatography mass spectrometer and an imaging mass spectrometry upgrade for a second existing high resolution mass spectrometer. The facility will break barriers currently limiting discovery and localisation of metabolic changes during plant and animal development under environmental stress; integral chemical signals exchanged in host-microbe interactions; and volatile signatures linked to ecosystem health and developmental anomalies in animals. Results will inform innovative strategies to enhance biological adaptation, climate resilience and plant, animal, and ecosystem health.Read moreRead less
Decision making for lifetime affordable and tenable city housing. This project will study home buying decisions and outcomes and use this to provide new insights into housing affordability and liveability. The project will develop an innovative software tool for Australia's home buyers to explore affordability and liveability during home buying, and agent-based modelling of scenarios for urban development futures.
Navigating brains: the neurobiology of spatial cognition. Navigation is one of the most crucial and most challenging problems animals face. Behavioural analyses have shown that animals make use of a number of different mechanisms to navigate, but very little is known of how different forms of spatial information are processed and integrated by the brain. The project aims to tackle this by placing tethered ants in a virtual-reality simulation of their real environment allowing precise control of ....Navigating brains: the neurobiology of spatial cognition. Navigation is one of the most crucial and most challenging problems animals face. Behavioural analyses have shown that animals make use of a number of different mechanisms to navigate, but very little is known of how different forms of spatial information are processed and integrated by the brain. The project aims to tackle this by placing tethered ants in a virtual-reality simulation of their real environment allowing precise control of visual navigational cues, as well as the opportunity to study the brains of the tethered ants as they solve the real-world challenge of finding home. This may reveal how simple brains efficiently solve navigational tasks, which may inform both cognitive biology and bio-inspired computation.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE160100090
Funder
Australian Research Council
Funding Amount
$250,000.00
Summary
Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object ....Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object recognition in images, speech recognition and automatic translation, bringing the prospect of machine intelligence closer than ever. Modern machine learning techniques have had huge impact in the last decade in fields such as robotics, computer vision and data analytics. The facility would enable Australian researchers to develop, learn and apply deep networks to problems of national importance in robotic vision and big data analytics. Read moreRead less
AI Planning: The Next Generation. This is a project in Artificial Intelligence. It aims at extending and integrating automated planning (and other forms of reasoning) with learning to produce a new generation of planning systems that are robust, safe, scalable, and trusted. These are some of the most significant issues to address to accelerate the adoption of planning systems in industry. Expected outcomes include a pipeline to learn rich symbolic planning models from narrated demonstration vide ....AI Planning: The Next Generation. This is a project in Artificial Intelligence. It aims at extending and integrating automated planning (and other forms of reasoning) with learning to produce a new generation of planning systems that are robust, safe, scalable, and trusted. These are some of the most significant issues to address to accelerate the adoption of planning systems in industry. Expected outcomes include a pipeline to learn rich symbolic planning models from narrated demonstration videos, new ways to represent, learn, and search for generalised policies that are scalable and robust, and approaches to verify and explain generalised policies. The new systems should benefit the aerospace industry by assisting humans in assembling and delivering aerospace products.Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH210100030
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
ARC Research Hub in Intelligent Robotic Systems for Real-Time Asset Management. This hub aims to transform the way assets and infrastructure are managed by developing new capabilities for intelligent robotic systems for inspection, monitoring, and maintenance. The hub expects to generate new knowledge in robotics and associated fields including sensing, planning, data processing, and machine learning using interdisciplinary approaches and tight collaboration between academia and industry. The ex ....ARC Research Hub in Intelligent Robotic Systems for Real-Time Asset Management. This hub aims to transform the way assets and infrastructure are managed by developing new capabilities for intelligent robotic systems for inspection, monitoring, and maintenance. The hub expects to generate new knowledge in robotics and associated fields including sensing, planning, data processing, and machine learning using interdisciplinary approaches and tight collaboration between academia and industry. The expected outcomes are robots with the ability to autonomously collect data for integration into a digital twin that provides a real-time representation of the true state of a physical asset. The benefits include both improved asset management and establishing Australia as a leading manufacturer of advanced robotic systems.Read moreRead less