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Field of Research : Other Artificial Intelligence
Australian State/Territory : NSW
Research Topic : genetic testing
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  • Funded Activity

    Discovery Projects - Grant ID: DP0208969

    Funder
    Australian Research Council
    Funding Amount
    $258,752.00
    Summary
    Kernel and Margin Based Machine Learning Algorithms. Certain machine learning algorithms, such as support vector machines, utilizing the ideas of large margins and kernels have attracted much attention lately because of their impressive performance on real world problems such as optical character recognition. We plan to refine and extend such algorithms to a wide range of different machine learning problems such as gene sequence analysis, image processing and text classification. Expected .... Kernel and Margin Based Machine Learning Algorithms. Certain machine learning algorithms, such as support vector machines, utilizing the ideas of large margins and kernels have attracted much attention lately because of their impressive performance on real world problems such as optical character recognition. We plan to refine and extend such algorithms to a wide range of different machine learning problems such as gene sequence analysis, image processing and text classification. Expected outcomes include the development of software that allows the solution of hitherto unsolved machine learning problems, and the ability to solve problems larger than those solvable by the current generation of machine learning tools.
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    Funded Activity

    Discovery Projects - Grant ID: DP0211282

    Funder
    Australian Research Council
    Funding Amount
    $50,000.00
    Summary
    Developing optimal synthesis strategies in distributed expert systems. The aim of this project is to investigate synthesis strategies in distributed expert systems (DESs). Such strategies are used to synthesize multiple solutions to the same task from different experts (either human experts or expert systerms) in order to obtain the final solution to the task. These strategies could be used in a wide application of domains such as insurance agencies and medical diagnosis systems. The expected .... Developing optimal synthesis strategies in distributed expert systems. The aim of this project is to investigate synthesis strategies in distributed expert systems (DESs). Such strategies are used to synthesize multiple solutions to the same task from different experts (either human experts or expert systerms) in order to obtain the final solution to the task. These strategies could be used in a wide application of domains such as insurance agencies and medical diagnosis systems. The expected outcomes are to develop computational strategies, neural network strategies, and case-based strategies for solving different synthesis cases.
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    Funded Activity

    Discovery Projects - Grant ID: DP0211847

    Funder
    Australian Research Council
    Funding Amount
    $203,000.00
    Summary
    The Physics of Network Computation. This project combines expertise in nonlinear soliton physics and computational sciences in order to provide new insights into the physics of network computation. Our proposal addresses the mathematics and computer modelling underlying nonconscious problem solving. We develop a new template concept, the meta-mode, which embodies the network structure of knowledge and the linking mechanisms, which underpin human creativity. We establish the optimal connectiv .... The Physics of Network Computation. This project combines expertise in nonlinear soliton physics and computational sciences in order to provide new insights into the physics of network computation. Our proposal addresses the mathematics and computer modelling underlying nonconscious problem solving. We develop a new template concept, the meta-mode, which embodies the network structure of knowledge and the linking mechanisms, which underpin human creativity. We establish the optimal connectivity distributions to preserve distinct pattern classes yet allow model radical shifts in paradigms, and develop algorithms for autonomous connectivity optimisation. We investigate nonlinear process such as solitons and random Boolean networks as realisations of these principles.
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    Funded Activity

    Linkage - International - Grant ID: LX0346249

    Funder
    Australian Research Council
    Funding Amount
    $15,000.00
    Summary
    Meta-Ontology based Protocols for the Cooperation in Heterogeneous Agent Systems. Cooperation and communication are two important research issues in the area of multi-agent systems and distributed artificial intelligence. The aim of this project is to study and develop meta-ontology based protocols for cooperation in multi-agent systems. The outcomes of the project include semantics of meta-ontology, a conceptual model to encompass the defined semantics, implementation of the model, and test res .... Meta-Ontology based Protocols for the Cooperation in Heterogeneous Agent Systems. Cooperation and communication are two important research issues in the area of multi-agent systems and distributed artificial intelligence. The aim of this project is to study and develop meta-ontology based protocols for cooperation in multi-agent systems. The outcomes of the project include semantics of meta-ontology, a conceptual model to encompass the defined semantics, implementation of the model, and test results in an open environment. The Key Laboratory of Intelligent Information Processing at Institute of Computing Technology, Chinese Academy of Sciences, is very active in the area of distributed artificial intelligence and agent technologies, and is an ideal partner for this project.
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