Multi-Agent Solutions for the Development of Self-Organised and Self-Adapted Distributed Energy Generation Systems. The project aims to develop a self-organised multi-agent framework for modelling Marco-Smart Grid (SMG), dynamic coordination mechanisms between SMGs in distributed energy systems, and self-adaptation approaches for SMGs and restoration strategies to detect and recover an SMG network from faults and outages. The significance of this project lies in its promise to solve the challeng ....Multi-Agent Solutions for the Development of Self-Organised and Self-Adapted Distributed Energy Generation Systems. The project aims to develop a self-organised multi-agent framework for modelling Marco-Smart Grid (SMG), dynamic coordination mechanisms between SMGs in distributed energy systems, and self-adaptation approaches for SMGs and restoration strategies to detect and recover an SMG network from faults and outages. The significance of this project lies in its promise to solve the challenging issues of Smart Grid (SG) in multi-agent research and provide practical solutions to the development of effective and higher-quality distributed energy-generation systems with renewable energy resources. The expected outcomes are a framework, models, mechanisms and approaches in SG research and their practical applications.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.
Discovery Early Career Researcher Award - Grant ID: DE120100995
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Visual navigation for sunny summer days and stormy winter nights. This project will develop innovative techniques for camera-based navigation that recognise locations under a wide range of environmental conditions caused by day-night cycles, weather and seasonal change. These techniques will enable the widespread use of cheap and lightweight cameras in robot and personal navigation systems.
Discovery Early Career Researcher Award - Grant ID: DE150101351
Funder
Australian Research Council
Funding Amount
$315,000.00
Summary
Playing and Solving General Games. Constructing rational agents for general dynamic decision problems is a long-standing open Artificial Intelligence challenge. An important milestone is to construct artificial agents that can learn and play new games well (universal playing agents). Specialised artificial intelligence systems are increasingly successful in domains such as Chess, Go, and Poker. The project aims to develop the theoretical and practical foundations of universal playing agents thro ....Playing and Solving General Games. Constructing rational agents for general dynamic decision problems is a long-standing open Artificial Intelligence challenge. An important milestone is to construct artificial agents that can learn and play new games well (universal playing agents). Specialised artificial intelligence systems are increasingly successful in domains such as Chess, Go, and Poker. The project aims to develop the theoretical and practical foundations of universal playing agents through a mathematical study of algorithms and heuristics for specific games. This project aims to significantly bridge the gap from efficient specialised players to high performance rational agents.Read moreRead less
Automated benthic understanding with multimodal observations. This project aims to deliver cost-effective techniques to explore and monitor marine environments. The project will develop novel methods for classification of large extent, multimodality seafloor surveys consisting of high-resolution visual 3D gigamosaics made of tens of thousands of images coregistered with broad-scale, lower resolution remote sensing data. This knowledge is essential for designing cost-effective, scalable systems t ....Automated benthic understanding with multimodal observations. This project aims to deliver cost-effective techniques to explore and monitor marine environments. The project will develop novel methods for classification of large extent, multimodality seafloor surveys consisting of high-resolution visual 3D gigamosaics made of tens of thousands of images coregistered with broad-scale, lower resolution remote sensing data. This knowledge is essential for designing cost-effective, scalable systems to explore, map and monitor Australia's marine environments. At a broader level, the approach and the techniques developed in this project have the potential to have applications in other areas such as terrestrial and intertidal ecology, extending positive impacts beyond benthic environments.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
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.
Robotics for zero-tillage agriculture. This project will develop small agricultural robots to increase broad-acre crop production and reduce environmental impact. These robots will have advanced navigation capability, will cooperate to cover large areas and resupply themselves, while causing less soil damage and applying herbicide more intelligently.
Inferring driver behaviours, intent and risk in complex traffic scenarios. This project intends to develop methods to evaluate risk during driving. The next generation of vehicles will be fitted with sophisticated perception and egocentric information. This will be combined with inter-vehicle communication enabling cooperative safety, used in conjunction with intelligent infrastructure. This technology is expected to be mandated in the United States starting from 2017. This project plans to deve ....Inferring driver behaviours, intent and risk in complex traffic scenarios. This project intends to develop methods to evaluate risk during driving. The next generation of vehicles will be fitted with sophisticated perception and egocentric information. This will be combined with inter-vehicle communication enabling cooperative safety, used in conjunction with intelligent infrastructure. This technology is expected to be mandated in the United States starting from 2017. This project plans to develop unsupervised learning algorithms to infer high-level driver behaviours, intent and contextual information to automatically evaluate levels of risk under complex driving scenarios. It plans to validate the results using naturalistic driving datasets taken in large-scale deployments around the world. This innovation may improve automotive safety and facilitate the deployment of autonomous vehicles.Read moreRead less