User-task co-adaptation for effective interactive simulation environments. This project aims to deliver smart interactive simulation environments in which users and simulation tasks work together. This project aims to create novel adaptive algorithms to automatically discover those user and task features that vary together to smartly adapt users and simulation tasks to work together harmoniously, seamlessly and effectively. Interactive simulation environments are the backbone for evaluating conc ....User-task co-adaptation for effective interactive simulation environments. This project aims to deliver smart interactive simulation environments in which users and simulation tasks work together. This project aims to create novel adaptive algorithms to automatically discover those user and task features that vary together to smartly adapt users and simulation tasks to work together harmoniously, seamlessly and effectively. Interactive simulation environments are the backbone for evaluating concepts, designs, products and advanced training systems in industry and government organisations. By bringing the user naturally inside the simulation as a task's component, users can improve their experience while task performance is simultaneously optimised. Intended outcomes include novel dynamic user-task profiling algorithms and new adaptive algorithms for user-task co-adaptation. Practical outcomes may include robust and highly effective simulation environments.Read moreRead less
Bio-inspired Computing for Problems with Dynamically Changing Constraints. The aim of this project is to design bio-inspired computing methods for dynamically changing environments. Dynamic problems arise frequently in the areas of engineering, logistics, and manufacturing. Such problems are usually subject to a large set of constraints that change over time due to changes in resources. Algorithms that can deal with such dynamic changes would benefit decision-makers. The project aims to provide ....Bio-inspired Computing for Problems with Dynamically Changing Constraints. The aim of this project is to design bio-inspired computing methods for dynamically changing environments. Dynamic problems arise frequently in the areas of engineering, logistics, and manufacturing. Such problems are usually subject to a large set of constraints that change over time due to changes in resources. Algorithms that can deal with such dynamic changes would benefit decision-makers. The project aims to provide a foundational theory as the basis for the design of bio-inspired algorithms dealing with dynamically changing constraints and provide approaches for dealing with important industrial problems.Read moreRead less
Fuzzy Transfer Learning for Prediction in Data-Shortage and Rapidly-Changing Environments. Collecting sufficient up-to-date data to train a learning model for data analysis and prediction is difficult and expensive. This project will develop a Fuzzy Transfer Learning methodology, using Information Granularity theory, that exploits data with different features and/or distributions available in other, similar systems, to provide accurate learning-based prediction for current problems. It will esta ....Fuzzy Transfer Learning for Prediction in Data-Shortage and Rapidly-Changing Environments. Collecting sufficient up-to-date data to train a learning model for data analysis and prediction is difficult and expensive. This project will develop a Fuzzy Transfer Learning methodology, using Information Granularity theory, that exploits data with different features and/or distributions available in other, similar systems, to provide accurate learning-based prediction for current problems. It will establish a new research direction, Fuzzy Transfer Learning for Prediction, and the outcomes will enable government and industry to better use past experience to make more accurate predictions and decisions. Highly significant benefits will also accrue in the data analytics, business intelligence and decision making research fields.Read moreRead less
Bio-inspired Computing for Problems with Chance Constraints. Bio-inspired algorithms have successfully been applied to a wide range of optimisation problems. Uncertainties in real-world applications can lead to critical failures of production schedules or safe critical systems. Chance constraints model such uncertainties and allow to limit the possibility of such failures. This future fellowship builds up the area of bio-inspired computing for problems with chance constraints. It develops high ....Bio-inspired Computing for Problems with Chance Constraints. Bio-inspired algorithms have successfully been applied to a wide range of optimisation problems. Uncertainties in real-world applications can lead to critical failures of production schedules or safe critical systems. Chance constraints model such uncertainties and allow to limit the possibility of such failures. This future fellowship builds up the area of bio-inspired computing for problems with chance constraints. It develops high performing bio-inspired algorithms for stochastic problems where the constraints can only be violated with a small probability. The outcomes will lead to more effective and reliable optimisation methods for complex planning processes in areas of national priority such as mining and manufacturing.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140100017
Funder
Australian Research Council
Funding Amount
$394,800.00
Summary
Adaptive Optimisation of Complex Combinatorial Problems. One of the most common problems faced by planners, whether in industry or government, is optimisation, finding the optimal solution to a problem. Even a one per cent improvement in a solution can make a difference of millions of dollars in some cases. Traditionally optimisation problems are solved by analytic means or exact optimisation methods. Today, however, many optimisation problems involve complex combinatorial systems that make such ....Adaptive Optimisation of Complex Combinatorial Problems. One of the most common problems faced by planners, whether in industry or government, is optimisation, finding the optimal solution to a problem. Even a one per cent improvement in a solution can make a difference of millions of dollars in some cases. Traditionally optimisation problems are solved by analytic means or exact optimisation methods. Today, however, many optimisation problems involve complex combinatorial systems that make such traditional approaches unsuitable or intractable. This project aims to assist researchers and practitioners in solving complex combinatorial optimisation problems by adapting the optimisation strategy to the problem being solved, based on problem features such as search space difficulty. Read moreRead less
Evolutionary diversity optimisation. This project aims to build up and establish the area of evolutionary diversity optimisation. The project will cover the design and application of evolutionary diversity optimisation methods to complex problems of significance and high national economic benefit and build up the theoretical foundations of these methods. The project is expected benefit decision makers by providing them a diverse set of high quality alternatives to choose from. This project will ....Evolutionary diversity optimisation. This project aims to build up and establish the area of evolutionary diversity optimisation. The project will cover the design and application of evolutionary diversity optimisation methods to complex problems of significance and high national economic benefit and build up the theoretical foundations of these methods. The project is expected benefit decision makers by providing them a diverse set of high quality alternatives to choose from. This project will allow them to make highly informed decisions and lead to more reliable solutions for optimisation problems, in areas of high economic impact such as manufacturing and supply chain management.Read moreRead less
Concept Drift Detection and Reaction for Data-driven Decision Making. Unforeseeable changes to patterns that underlie data (concept drift) occur in all organisational data, and in unstructured data, making subsequent data-driven prediction less accurate as time passes, which leads to poor decision outcomes. To solve these problems, this project aims to develop novel fuzzy competence models to reflect concept drift, with methods to detect and react to changes, and integrate them into Decision Sup ....Concept Drift Detection and Reaction for Data-driven Decision Making. Unforeseeable changes to patterns that underlie data (concept drift) occur in all organisational data, and in unstructured data, making subsequent data-driven prediction less accurate as time passes, which leads to poor decision outcomes. To solve these problems, this project aims to develop novel fuzzy competence models to reflect concept drift, with methods to detect and react to changes, and integrate them into Decision Support Systems (DSS) to provide adaptivity for ever-changing environments. These cutting-edge results are intended to be directly used to enhance organisational real-time data analytics and dynamic decision making, and are expected to significantly contribute to information science by introducing a new research field, adaptive data-driven DSS.Read moreRead less
Parameterized Analysis of Bio-inspired Computing - From Theory to High Performing Algorithms. This project will establish the field of parameterised analysis of bio-inspired computing which includes prominent approaches such as evolutionary algorithms and ant colony optimisation. It will rigorously analyse features of instances of combinatorial optimisation problems and their impact on the runtime behaviour of bio-inspired computing methods. Furthermore, the project will design new bio-inspired ....Parameterized Analysis of Bio-inspired Computing - From Theory to High Performing Algorithms. This project will establish the field of parameterised analysis of bio-inspired computing which includes prominent approaches such as evolutionary algorithms and ant colony optimisation. It will rigorously analyse features of instances of combinatorial optimisation problems and their impact on the runtime behaviour of bio-inspired computing methods. Furthermore, the project will design new bio-inspired computing algorithms that make use of instance features and hardness characteristics. The results will advance the theoretical knowledge of bio-inspired computing, bridge the gap between theory and practice, and provide more powerful algorithms for complex optimisation problems occurring for example in the field of supply chain management for the mining industry.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160100850
Funder
Australian Research Council
Funding Amount
$330,000.00
Summary
Dynamic adaptive software configuration. The aim of this project is to use computational intelligence in software engineering processes to achieve self-optimising products. Many mobile device users bemoan inadequate battery life, and device size is largely determined by the battery. In addition, information and communications technology uses six per cent of the global electricity production. The expected outputs of this project will be packages of optimisation components that software engineers ....Dynamic adaptive software configuration. The aim of this project is to use computational intelligence in software engineering processes to achieve self-optimising products. Many mobile device users bemoan inadequate battery life, and device size is largely determined by the battery. In addition, information and communications technology uses six per cent of the global electricity production. The expected outputs of this project will be packages of optimisation components that software engineers can incorporate into next generation products: the products analyse their collected usage data, perform what-if analyses, and optimise their configurations accordingly for the next usage period. Hence, the products may respond faster, be more reliable, and consume less energy.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