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Research Topic : Separation Science
Field of Research : Decision Making
Australian State/Territory : SA
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  • Funded Activity

    Discovery Projects - Grant ID: DP150104206

    Funder
    Australian Research Council
    Funding Amount
    $330,500.00
    Summary
    Learning and choosing in a complex world. How do people make choices in a complex world? Making good choices requires expertise, but people must often forego rewards in order to acquire this knowledge. This is the essence of an "explore-exploit dilemma": to maximise rewards across a long time frame, people must take the time to explore and learn now. Empirically, this project aims to unify much of the existing psychological literature and extend it to cover richer, more complex problems. Theoret .... Learning and choosing in a complex world. How do people make choices in a complex world? Making good choices requires expertise, but people must often forego rewards in order to acquire this knowledge. This is the essence of an "explore-exploit dilemma": to maximise rewards across a long time frame, people must take the time to explore and learn now. Empirically, this project aims to unify much of the existing psychological literature and extend it to cover richer, more complex problems. Theoretically, the project aims to use tools from machine learning to compare human decision making to optimal planning models.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP190102708

    Funder
    Australian Research Council
    Funding Amount
    $180,000.00
    Summary
    Expecting the unexpected: how people prioritise predictability. This project aims to investigate how people represent and use information about unpredictability in their environment. Seeing too much predictability is problematic, but seeing too little can also be a problem, for example inappropriate "learned helplessness" can occur, whereby people feel disempowered because the world is seen as random. Recent findings demonstrated a bias in fundamental learning that may maintain these inappropria .... Expecting the unexpected: how people prioritise predictability. This project aims to investigate how people represent and use information about unpredictability in their environment. Seeing too much predictability is problematic, but seeing too little can also be a problem, for example inappropriate "learned helplessness" can occur, whereby people feel disempowered because the world is seen as random. Recent findings demonstrated a bias in fundamental learning that may maintain these inappropriate beliefs about unpredictability. This bias is not anticipated by formal theories of learning. The project will investigate how this bias is brought about by first formalising a novel theory of fundamental learning and then systematically testing its assumptions.
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    Funded Activity

    Linkage Projects - Grant ID: LP160101460

    Funder
    Australian Research Council
    Funding Amount
    $311,000.00
    Summary
    Developing group-based elicitation methods to improve decision making. This project aims to develop an elicitation methodology enabling multiple members of a team to contribute to the same technical problem - enabling expertise to be accurately combined while avoiding group and individual sources of bias. Good elicitation methods minimise bias in estimates and forecasts - which otherwise erode value and lead to sub-optimal decision making. Existing methods, however, ignore group structures; that .... Developing group-based elicitation methods to improve decision making. This project aims to develop an elicitation methodology enabling multiple members of a team to contribute to the same technical problem - enabling expertise to be accurately combined while avoiding group and individual sources of bias. Good elicitation methods minimise bias in estimates and forecasts - which otherwise erode value and lead to sub-optimal decision making. Existing methods, however, ignore group structures; that is that decisions made by, or on, the advice of teams have different characteristics than individual decisions and often preclude the use of methods designed to limit individuals' biases. By encoding the method into a computerised tool the project will assist public and private sector enterprises to improve group decision making.
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    Funded Activity

    Discovery Projects - Grant ID: DP150101094

    Funder
    Australian Research Council
    Funding Amount
    $534,209.00
    Summary
    Uncovering the processes underlying human reasoning: A state-trace approach. This project aims to answer the most important unresolved question in the psychology of reasoning; how many distinct cognitive processes underlie human reasoning? To answer this question, this project aims to conduct an extensive experimental investigation of the factors that selectively impact inductive and deductive inferences and the application of high-dimensional state-trace analysis; a powerful new method for diag .... Uncovering the processes underlying human reasoning: A state-trace approach. This project aims to answer the most important unresolved question in the psychology of reasoning; how many distinct cognitive processes underlie human reasoning? To answer this question, this project aims to conduct an extensive experimental investigation of the factors that selectively impact inductive and deductive inferences and the application of high-dimensional state-trace analysis; a powerful new method for diagnosing underlying processes from behavioural data. The project is expected also to develop a new computational model that accounts for both inductive and deductive forms of reasoning.
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    Funded Activity

    Discovery Projects - Grant ID: DP180103600

    Funder
    Australian Research Council
    Funding Amount
    $290,011.00
    Summary
    Where do inductive biases come from? A Bayesian investigation. This project aims to investigate the origin of our thinking and learning biases using state-of-the-art mathematical models and sophisticated experimental designs. Expected outcomes include bridging the gap between human and machine learning by pairing mathematical modelling with experimental work, forming a necessary step toward the development of machine systems that can reason like people do. This will provide significant benefits .... Where do inductive biases come from? A Bayesian investigation. This project aims to investigate the origin of our thinking and learning biases using state-of-the-art mathematical models and sophisticated experimental designs. Expected outcomes include bridging the gap between human and machine learning by pairing mathematical modelling with experimental work, forming a necessary step toward the development of machine systems that can reason like people do. This will provide significant benefits such as understanding how people operate so effectively in real environments, when even the most powerful computers struggle to handle the complexities of everyday learning problems.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP200100655

    Funder
    Australian Research Council
    Funding Amount
    $296,113.00
    Summary
    Improving the diagnosticity of eyewitness memory choices. Eyewitness identification error is common and costly. This project aims to improve the quality of information provided by eyewitnesses, and the ability of police officers and triers of fact (e.g., juries, judges) to evaluate this information. Laboratory investigations will determine how best to test memory and confidence to achieve this aim. A new class of cognitive models will provide a unified account of response accuracy, response time .... Improving the diagnosticity of eyewitness memory choices. Eyewitness identification error is common and costly. This project aims to improve the quality of information provided by eyewitnesses, and the ability of police officers and triers of fact (e.g., juries, judges) to evaluate this information. Laboratory investigations will determine how best to test memory and confidence to achieve this aim. A new class of cognitive models will provide a unified account of response accuracy, response time, and confidence, suitable for application to computerized testing scenarios. The models and testing methods validated in the laboratory will be refined for application in eyewitness memory settings, facilitating better evaluation of identification evidence, and potentially reducing wrongful convictions.
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    Showing 1-6 of 6 Funded Activites

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