- Title
- Understanding the architecture and capacity of cognitive systems
- Creator
- Howard, Zachary L.
- Relation
- University of Newcastle Research Higher Degree Thesis
- Resource Type
- thesis
- Date
- 2020
- Description
- Research Doctorate - Doctor of Philosophy (PhD)
- Description
- Human behavior is dictated by the world around us, and the world around us is complex. To fully understand the human brain we need to understand how individual cognitive processes operate in these complex environments. In this thesis I investigate cognitive processes in `complex' scenarios in which there are multiple stimuli to process. I present a body of work that both (a) furthers the methodology and statistical tools to study multi-stimulus processes, specifically the nature of the processing architecture and capacity, and (b) contributes to a number of theoretically important research questions pertaining to both of those properties of cognitive processes. Through the Methodology Stream I show limitations of current approaches for assessing processing architecture and capacity in multi-stimulus tasks, highlight errors in previously published statistical tools, and develop novel solutions to all raised concerns. In the Theoretical Stream I contribute important evidence regarding the nature of processing capacity, and resolve an existing question about processing architecture in memory searches defined by multiple constraints. The developments in this thesis have fundamental implications for both existing and future studies of workload capacity and processing architecture and will enable future research to address previously untestable questions.
- Subject
- sft; modeling; cognition; workload; architecture
- Identifier
- http://hdl.handle.net/1959.13/1412535
- Identifier
- uon:36495
- Rights
- Copyright 2020 Zachary L. Howard
- Language
- eng
- Full Text
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Thumbnail | File | Description | Size | Format | |||
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View Details Download | ATTACHMENT01 | Thesis | 7 MB | Adobe Acrobat PDF | View Details Download | ||
View Details Download | ATTACHMENT02 | Abstract | 172 KB | Adobe Acrobat PDF | View Details Download |