Special Research Initiatives - Grant ID: SR0354513
Funder
Australian Research Council
Funding Amount
$20,000.00
Summary
The Computational Processing of Human Language. Language is what makes us distinctly human; consequently, language attracts interest from many fields of research, particularly linguistics, psychology, and cognitive science. Moreover, language is the primary medium for the storage and dissemination of knowledge, a fact that has drawn many computer scientists to attempt to process, analyse and understand language. This network will bridge the many disciplines that are concerned with language, ex ....The Computational Processing of Human Language. Language is what makes us distinctly human; consequently, language attracts interest from many fields of research, particularly linguistics, psychology, and cognitive science. Moreover, language is the primary medium for the storage and dissemination of knowledge, a fact that has drawn many computer scientists to attempt to process, analyse and understand language. This network will bridge the many disciplines that are concerned with language, explore new ways in which computational models inform our understanding of human languages, and exploit new opportunities for applying theories of language in the development of human language technologies.Read moreRead less
The Psychology of Misinformation—Towards A Theory-driven Understanding. The project aims to develop a psychological theory of misinformation effects. Misinformation influences people’s memory, reasoning and decision-making even after corrections – it thus poses a significant challenge for science and society. Through the combination of systematic experimentation with theory-driven computational modelling, the project will strive to concurrently consider individual-level cognition and the impact ....The Psychology of Misinformation—Towards A Theory-driven Understanding. The project aims to develop a psychological theory of misinformation effects. Misinformation influences people’s memory, reasoning and decision-making even after corrections – it thus poses a significant challenge for science and society. Through the combination of systematic experimentation with theory-driven computational modelling, the project will strive to concurrently consider individual-level cognition and the impact of sociocultural context. It is anticipated that this novel integrative approach will substantially expand our understanding of misinformation effects, and that this theoretical progress will result in the formulation of specific communication strategies to reduce the impact of misinformation on society.Read moreRead less
The dog that didn't bark: a Bayesian account of reasoning from censored data. This project aims to develop and test a new computational theory of inductive reasoning. Inductive reasoning involves extending knowledge from known to novel instances, and is a central component of intelligent behaviour. This project will address the cognitive mechanisms that allow people to draw inferences based on both observed and censored evidence. The project intends to test the model through an extensive program ....The dog that didn't bark: a Bayesian account of reasoning from censored data. This project aims to develop and test a new computational theory of inductive reasoning. Inductive reasoning involves extending knowledge from known to novel instances, and is a central component of intelligent behaviour. This project will address the cognitive mechanisms that allow people to draw inferences based on both observed and censored evidence. The project intends to test the model through an extensive program of experimental investigation and computational modelling. The anticipated benefits include an enhanced understanding of human inference, especially in domains such as the evaluation of forensic or financial evidence, where data censoring is common.Read moreRead less
Developing a Unified Theory of Episodic Memory. This project aims to develop a model of episodic memory and to apply the model to both adult and child development data. Unlike current approaches, the model is expected to address multiple memory tasks including item recognition, associative recognition, source recognition and cued recall, and also aims to address reaction time data, allowing different sources of interference causing forgetting in adults to be identified. By addressing both encodi ....Developing a Unified Theory of Episodic Memory. This project aims to develop a model of episodic memory and to apply the model to both adult and child development data. Unlike current approaches, the model is expected to address multiple memory tasks including item recognition, associative recognition, source recognition and cued recall, and also aims to address reaction time data, allowing different sources of interference causing forgetting in adults to be identified. By addressing both encoding and retrieval processes, the model can assess how changes in different sources of interference modulate performance through the trajectory of early development. Hierarchical Bayesian estimation aims to enable a simultaneous account of multiple tasks and support future deployment in applied contexts.Read moreRead less