Visual search as a queueing process


Li, Yiqi


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URL: https://madoc.bib.uni-mannheim.de/53040
URN: urn:nbn:de:bsz:180-madoc-530406
Document Type: Doctoral dissertation
Year of publication: 2019
Place of publication: Mannheim
University: Universität Mannheim
Evaluator: Erdfelder, Edgar
Date of oral examination: 26 August 2019
Publication language: English
Institution: School of Social Sciences > Kognitive Psychologie u. Differentielle Psychologie (Erdfelder)
School of Business Informatics and Mathematics > Mathematische Statistik (Schlather 2012-)
Subject: 150 Psychology
300 Social sciences, sociology, anthropology
510 Mathematics
Keywords (English): visual search , queueing models , serial/parallel processing , RT distribution modeling , error modeling , stochastic modeling of cognitive processes , Monte Carlo simulation based parameter estimation
Abstract: A mathematical model accounting for both accuracy and response time (RT) data in standard visual search experiments on a distributional level has been developed. The model implements the conceptualization of Moore and Wolfe(2001) of a hybrid model, in which visual stimuli are selected by attention one after another and then identified in parallel. For the modeling of RT data on a distributional level, a finite-time queueing model with exponentially distributed interarrival times and service times, c parallel servers and a finite customer source is specified. It characterizes both the serial and parallel aspects of the visual search process by modeling it as a queueing system where stimuli enter serially and are processed in parallel at multiple servers. For the modeling of accuracy data, the queueing model is extended by integrating a mechanism that produces incorrect system responses. It differentiates between genuine processing errors and decision errors due to incomplete search. The observer is assumed to adapt a discrimination criterion for stimulus identification and a termination rule of search that both depend on set size to optimize search efficiency. The termination rule derived based on optimal foraging theory regulates the termination of the queueing process. Embedded in the queueing model, this mechanism accounts for both error rates and error RTs. Parameter estimation methods are developed using the maximum likelihood estimation (MLE) approach for accuracy-related parameters and the minimum distance estimation (MDE) approach based on Monte Carlo simulation for RT-related parameters. The complete model is fitted to two empirical data sets of two different search tasks. For both tasks, it fits the error rates precisely and the distributional RT data nicely, indicating a high explanatory power of the model.

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Li, Yiqi (2019) Visual search as a queueing process. Open Access Mannheim [Doctoral dissertation]
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