archives@tulane.edu / Heuristics allow us to navigate a complex and uncertain world, react to new situations, and make decisions without needing all the information. While this is often helpful, using heuristics can sometimes lead to biased actions and potentially costly errors. Many algorithms are developed with the goal of improving human performance: either by offering recommendations or by seeking to predict and thereby mitigate human error. Such tools benefit when they can account for human bias and behavior, either through analysis of behavioral data in the design process or by incorporating computational cognitive models that simulate and predict behavior. This dissertation explores several novel computational approaches for simulating bias and heuristics in human behavior at different cognitive levels of abstraction. First, we develop a model of attentional bias in spatial auditory attention for the cognitive architecture, ACT-R. We then move to a more complex task, modeling confirmation bias that occurs when making decisions with noisy feedback. Finally, we consider behavior in a multi-agent setting, collecting and analyzing experimental data about heuristics in voting. In all three instances, we implement different computational models of human behavior to evaluate them on behavioral data. This work provides tools that support a better understanding of human behavior and enables the integration of bias and heuristics in human-aware computing, laying the groundwork for designing new computational approaches inspired by human heuristic behavior. / 1 / Jaelle Scheuerman
Identifer | oai:union.ndltd.org:TULANE/oai:http://digitallibrary.tulane.edu/:tulane_120372 |
Contributors | (author), (Thesis advisor), School of Science & Engineering Computer Science (Degree granting institution) |
Publisher | Tulane University |
Source Sets | Tulane University |
Language | English |
Detected Language | English |
Type | Text |
Format | electronic, pages: 127 |
Rights | No embargo, Copyright is in accordance with U.S. Copyright law. |
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