Generating automated predictions of behavior strategically adapted to specific performance objectives

Eng, Katherine; Lewis, Richard L.; Tollinger, Irene; Chu, Alina; Howes, Andrew; Vera, Alonso

doi:10.1145/1124772.1124866

Cited by 18 publications

(13 citation statements)

References 15 publications

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“…Eng et al [4] focused on the question of evaluating two different designs for a flight deck control panel. They demonstrated that performance measures and objective functions could play a key role in modeling behavior: Predictions could be shaped not only by basic task goals and the constraints on the cognitive architecture, but also by the specific performance objectives (e.g., minimizing task completion time or working memory load).…”

Section: Modeling Human Multitaskingmentioning

confidence: 99%

“…Another recent approach, cognitive constraint modeling (CCM), posits that predictions of behavior can be derived by finding the set of optimal strategies given an objective function, a set of plausible strategies, and a set of constraints on human performance [7,8]. CCM facilitates exploration of strategic variations in behavior and allows for objective functions to represent desired trade-offs in performance (e.g., between working memory load and task completion time [4]). One feature of the CCM approach is the demand for a quantitative analysis of the constraints imposed by interaction with the task environment.…”

Section: Introductionmentioning

confidence: 99%

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A cognitive constraint model of dual-task trade-offs in a highly dynamic driving task

Brumby

Howes

Salvucci

2007

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

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The paper describes an approach to modeling the strategic variations in performing secondary tasks while driving. In contrast to previous efforts that are based on simulation of a cognitive architecture interacting with a task environment, we take an approach that develops a cognitive constraint model of the interaction between the driver and the task environment in order to make inferences about dual-task performance. Analyses of driving performance data reveal that a set of simple equations can be used to accurately model changes in the lateral position of the vehicle within the lane. The model quantifies how the vehicle's deviation from lane center increases during periods of inattention, and how the vehicle returns to lane center during periods of active steering. We demonstrate the benefits of the approach by modeling the dialing of a cellular phone while driving, where drivers balance the speed in performing the dial task with accuracy (or safety) in keeping the vehicle centered in the roadway. In particular, we show how understanding, rather than simulating, the constraints imposed by the task environment can help to explain the costs and benefits of a range of strategies for interleaving dialing and steering. We show how particular strategies are sensitive to a combination of internal constraints (including switch costs) and the trade-off between the amount of time allocated to secondary task and the risk of extreme lane deviation.

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Section: Modeling Human Multitaskingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A cognitive constraint model of dual-task trade-offs in a highly dynamic driving task

Brumby

Howes

Salvucci

2007

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Self Cite

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“…Recent efforts to understand, what Payne, Howes and Reader [28] call interactive search tasks, have included [5,6,8,13,31]. However, it is sometimes difficult to ascertain which interface will be best when the details of the strategy that people will use given a particular task environment are unclear [10,14,17,19]. In this paper we are interested in the strategy choices that people make about visual search, i.e.…”

Section: Introductionmentioning

confidence: 99%

The adaptation of visual search strategy to expected information gain

Tseng

Howes

2008

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

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An important question for Human-Computer Interaction is to understand how and why visual search strategy is adapted to the demands imposed by the task of searching the results of a search engine. There is emerging evidence that a key part of the answer concerns the expected information gain of each of the set of available information gathering actions. We build on previous research to show that people are acutely sensitive to differences in the density and in the number of items returned by the search engine. These factors cause shifts in the efficiency of the available information gathering actions. We focus on an image browsing task, and show that, as a consequence of changes to the efficiency of available actions, people make small but significant changes to eye-movement strategy.

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“…The constraint-based optimising reasoning engine system (CORE) [22,34,86] takes a different approach to model cognition. Instead of a rule-based system, it models cognition as a set of constraints and an objective function.…”

Section: Cognitive Modellingmentioning

confidence: 99%

Towards standardisation of user models for simulation and adaptation purposes

Kaklanis

Biswas

Mohamad

et al. 2014

Univ Access Inf Soc

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The use of user models can be very valuable when trying to develop accessible and ergonomic products and services taking into account users specific needs and preferences. Simulation of userproduct interaction using user models may reveal accessibility issues at the early stages of design and development, and this results to a significant reduction in costs and development time. Moreover, user models can be used in adaptive interfaces enabling the personalised customisation of user interfaces that enhances the accessibility and usability of products and services. This paper presents the efforts of the Virtual User Modelling and Simulation Standardisation VUMS cluster of projects towards the development of an interoperable user model, able to describe both able-bodied and people with various kinds of disabilities. The VUMS cluster is consisted by the VERITAS, MyUI, GUIDE, and VICON FP7 European projects, all involved in user modelling from different perspectives. The main goal of the VUMS cluster was the development of a unified user model that could be used by all the participant projects and that could be the basis of a new user model standard. Currently, within the VUMS cluster, a common user model has been defined and converters that enable the transformation from each projects specific user model to the VUMS user model and vice versa have been developed enabling, thus, the exchange of user models between the projects

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Generating automated predictions of behavior strategically adapted to specific performance objectives

Cited by 18 publications

References 15 publications

A cognitive constraint model of dual-task trade-offs in a highly dynamic driving task

A cognitive constraint model of dual-task trade-offs in a highly dynamic driving task

The adaptation of visual search strategy to expected information gain

Towards standardisation of user models for simulation and adaptation purposes

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