ARC Centre of Excellence for Robotic Vision. Robots are vital to Australia's future prosperity in the face of high relative wages, low or decreasing productivity, and impending labour shortages. However the work and workplaces of our most important industries are unstructured and changeable and current robots are challenged by their inability to quickly, safely and reliably "see" and "understand" what is around them. The Centre's research will create the fundamental science and technologies th ....ARC Centre of Excellence for Robotic Vision. Robots are vital to Australia's future prosperity in the face of high relative wages, low or decreasing productivity, and impending labour shortages. However the work and workplaces of our most important industries are unstructured and changeable and current robots are challenged by their inability to quickly, safely and reliably "see" and "understand" what is around them. The Centre's research will create the fundamental science and technologies that will allow robots to see as we do, and overcome the last barrier to the ubiquitous deployment of robots into society for the benefit of all.Read moreRead less
Enabling small businesses to more cost-effectively use big data on cloud computing platforms. This project will invent a new generic cost model for managing big data in cloud computing. This model will enable agent-based, innovative data management technologies to reduce the cost of storage, computation and bandwidth consumption in the cloud. Outcomes will enable small businesses to use big data in cloud computing more cost effectively.
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.
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
Tools, methodologies and reasoning support for developing companion-toy modules. This project investigates building of modules for an intelligent Toy which can be customised and adapted over time by add-on modules. Intelligent interactive toys are growing in popularity, and the ability for such a toy to develop over a prolonged lifetime, is both a sound business idea and a mechanism for extending the useful life of the Toy.
Integrating and automating testing in multi-agent system development. This research will provide mechanisms that facilitate easier and more thorough testing of multi-agent systems. Multi-agent technology is extremely powerful and can save businesses substantial time and effort in developing complex systems. Automated testing will ensure that systems built using this technology are more robust, and will also enable substantial savings in time required for testing. Multi agent systems are notorio ....Integrating and automating testing in multi-agent system development. This research will provide mechanisms that facilitate easier and more thorough testing of multi-agent systems. Multi-agent technology is extremely powerful and can save businesses substantial time and effort in developing complex systems. Automated testing will ensure that systems built using this technology are more robust, and will also enable substantial savings in time required for testing. Multi agent systems are notoriously difficult to test, due to their complexity. However the approaches used in this project will enable intelligent generation of test cases that are potentially difficult, and also generation of test cases that are based on specified functionality.Read moreRead less
Responsive automated negotiation in open distributed environments. The outcomes of this project will be of central importance to a wide range of application areas such as service economy, smart energy grids and smart transportation. The work proposed here will enable the information technology industry to utilise distributed systems and agent technologies in developing the software-driven knowledge economy of the twenty-first-century.
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.
Explanation in artificial intelligence: a human-centred approach. This project aims to produce validated methods for creating human-centred explanations of decisions made by artificial intelligence (AI). Trial deployment of AI devices has resulted in the requirement for explanations of how AI makes decisions, where developed AI systems gave insufficient consideration of how decision logic would be explained to people. This project positions 'explainable AI' within the intersection of human-compu ....Explanation in artificial intelligence: a human-centred approach. This project aims to produce validated methods for creating human-centred explanations of decisions made by artificial intelligence (AI). Trial deployment of AI devices has resulted in the requirement for explanations of how AI makes decisions, where developed AI systems gave insufficient consideration of how decision logic would be explained to people. This project positions 'explainable AI' within the intersection of human-computer interaction, computer science and cognitive psychology. The expected outcomes of this project are new methods, models and algorithms for explaining different types of AI models to people. This project should result in improved understanding and trust of decisions made by AI systems, mitigating some societal concerns about AI-based decision making.Read moreRead less
Spoken conversational search: contextual interactive techniques to support effective information search over a speech-only communication channel. This project will develop new techniques for effective information search using speech only, supporting improved information access for visually impaired people or in situations that require focused visual attention (e.g. driving). The techniques are based on a conversational approach to information search and presentation of results.