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Research Topic : working memory
Field of Research : Knowledge Representation And Machine Learning
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Knowledge Representation And Machine Learning (6)
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  • Funded Activity

    Discovery Projects - Grant ID: DP0556847

    Funder
    Australian Research Council
    Funding Amount
    $135,000.00
    Summary
    Discrimination learning in humans: Associative and attentional mechanisms. This project offers three major benefits: (1) Australian researchers excel in cognitive neuroscience, learning and psychopharmacology, areas based largely on animal models of human cognition. This project contributes to these areas by specifying the relationship between animal learning and human cognition; (2) the project enhances Australia's international reputation in these areas via its collaboration with a scientist .... Discrimination learning in humans: Associative and attentional mechanisms. This project offers three major benefits: (1) Australian researchers excel in cognitive neuroscience, learning and psychopharmacology, areas based largely on animal models of human cognition. This project contributes to these areas by specifying the relationship between animal learning and human cognition; (2) the project enhances Australia's international reputation in these areas via its collaboration with a scientist of Geoff Hall's stature; it also offers students outstanding research training and international exposure; (3) given Chris Mitchell's industry experience and the relevance of this work to advertising/marketing, this project will generate knowledge relevant to, and possible future collaborations with, Australian industries.
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    Funded Activity

    Linkage Projects - Grant ID: LP0347319

    Funder
    Australian Research Council
    Funding Amount
    $69,099.00
    Summary
    The Development of Creative Thinking Ability in TAFE Design Students. The aim is to develop an instructional framework as a conceptual basis for instruction aimed at TAFE design student use of imagery in creative thinking. The research addresses the challenges of recent post-compulsory education initiatives, which include a more specific focus on the development of creative problem-solving skills, but provide little guidance on instructional strategies. The research will synthesise the framewo .... The Development of Creative Thinking Ability in TAFE Design Students. The aim is to develop an instructional framework as a conceptual basis for instruction aimed at TAFE design student use of imagery in creative thinking. The research addresses the challenges of recent post-compulsory education initiatives, which include a more specific focus on the development of creative problem-solving skills, but provide little guidance on instructional strategies. The research will synthesise the framework from theories about cognitive processes, creative problem-solving and the use of mental imagery; and the results of an imagery training program and creative problem-solving interventions. The outcome will be an instructional framework for guiding the development of student creative thinking in design-based courses in TAFE.
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    Funded Activity

    Discovery Projects - Grant ID: DP0211406

    Funder
    Australian Research Council
    Funding Amount
    $45,000.00
    Summary
    Evaluating models of category learning that use general feature-based representations. Three competing models of human category learning will be evaluated by comparing their behaviour to human performance on an experimental task where each model makes qualitatively different predictions. A series of theoretical and algorithmic advances will be undertaken to ensure each of the category learning models uses the same feature-based representation. Because the three models propose very different lear .... Evaluating models of category learning that use general feature-based representations. Three competing models of human category learning will be evaluated by comparing their behaviour to human performance on an experimental task where each model makes qualitatively different predictions. A series of theoretical and algorithmic advances will be undertaken to ensure each of the category learning models uses the same feature-based representation. Because the three models propose very different learning processes, their comparison will give insight into the basic cognitive process of categorisation. The algorithms for generating feature representations and modelling human category learning will also have potential for application in data visualisation and information handling systems.
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    Funded Activity

    Linkage Projects - Grant ID: LP0562206

    Funder
    Australian Research Council
    Funding Amount
    $150,000.00
    Summary
    Psychological User Profiling in the Telecommunications Industry. Recording user behaviour allows businesses to learn about their customers. This is particularly important in telecommunications, since the core business involves a large number of users who vary considerably from one another. This project combines psychological insights with modern statistical methods to develop a psychologically plausible user profiling framework, accounting for the idiosyncratic usage patterns of customers, and t .... Psychological User Profiling in the Telecommunications Industry. Recording user behaviour allows businesses to learn about their customers. This is particularly important in telecommunications, since the core business involves a large number of users who vary considerably from one another. This project combines psychological insights with modern statistical methods to develop a psychologically plausible user profiling framework, accounting for the idiosyncratic usage patterns of customers, and the way in which they change over time. The profiles will be tied to marketing prospects through interviews and surveys. Applied benefits include the ability to predict, understand and act upon user behaviour. The project also adds substantially to theories of memory, individual differences and decision-making.
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    Funded Activity

    Discovery Projects - Grant ID: DP0773794

    Funder
    Australian Research Council
    Funding Amount
    $510,000.00
    Summary
    Hierarchical Bayesian Models for Human Conceptual Learning. This project seeks to understand the nature of human conceptual learning. With the shift to an information-based economy, it becomes important to understand what assumptions a real-world learning system should make. Even given the impressive growth of machine learning and artificial intelligence, the human mind remains the most successful example of such a system. In this light, the scientific study of human conceptual structure present .... Hierarchical Bayesian Models for Human Conceptual Learning. This project seeks to understand the nature of human conceptual learning. With the shift to an information-based economy, it becomes important to understand what assumptions a real-world learning system should make. Even given the impressive growth of machine learning and artificial intelligence, the human mind remains the most successful example of such a system. In this light, the scientific study of human conceptual structure presents the opportunity to discover how an intelligent thinking system should operate. In addition, many important problems facing an information economy involve being able to understand how people behave. An understanding of the concepts people use is central to this endeavour.
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    Funded Activity

    Discovery Projects - Grant ID: DP0346379

    Funder
    Australian Research Council
    Funding Amount
    $152,000.00
    Summary
    The role of memory and reasoning processes in associative learning. The project will investigate how people learn to detect cues that predict or cause significant events in their environment (associative learning). The research builds on recent empirical and theoretical work by the investigators supporting the role of deductive reasoning processes in associative learning. Novel experimental strategies will be used to identify the separate and interacting roles of lower-level memory processes a .... The role of memory and reasoning processes in associative learning. The project will investigate how people learn to detect cues that predict or cause significant events in their environment (associative learning). The research builds on recent empirical and theoretical work by the investigators supporting the role of deductive reasoning processes in associative learning. Novel experimental strategies will be used to identify the separate and interacting roles of lower-level memory processes and higher-level reasoning processes. Existing competing models and novel cooperative models will be tested. The research will lead to a better understanding of associative learning in humans, and will also inform the construction of intelligent artificial systems.
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