Michael J. Schoelles

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Soft constraints hypothesis (SCH) is a rational analysis approach that holds that the mixture of perceptual-motor and cognitive resources allocated for interactive behavior is adjusted based on temporal cost-benefit tradeoffs. Alternative approaches maintain that cognitive resources are in some sense protected or conserved in that greater amounts of(More)
Argus simulates a radar-like target classification task. It was developed to support research in measuring and modeling cognitive work load. Argus is used in both single-subject and team modes. However, the Argus system is more than just a simulated task environment. Argus features flexible experimenter control over cognitive work load, as well as extensive(More)
Cognition, perception, and motor actions weave a tangled web. At times, the three may proceed independently of each other. At other times, they may have complex, sequential dependencies such as, for example, when the decision to click on a button waits for perception to return to cognition the information that the cursor and button objects are co-located.(More)
Small variations in how a task is designed can lead humans to tradeoff interaction-intensive for memory-intensive strategies. In this paper we introduce one such task, Blocks World, and present empirical data that shows such tradeoffs. Our attempts to model the acquisition of these tradeoffs using the default ACT-R conflict resolution mechanisms have met(More)
We explore the utility of functional Near Infra Red (fNIR) technology in providing both empirical support and a basis for assessing and predicting dynamic changes in cognitive workload within the theoretical context of computational cognitive modeling (CCM). CCM has had many successes and in recent years has expanded from a tool for basic research to one(More)
Milliseconds matter – when the interface permits, users will adjust their behavior to shave 100-200 msec from low level interactions. Saving milliseconds involves deploying different microstrategies. These strategies are deployed automatically; that is, non-deliberately. To explore the ability of people to maximize performance by deploying different(More)
Our work with the Argus Prime (Schoelles & Gray, 2001) simulated task environment has uncovered a variety of strategies that subjects use, at least sometimes, during target acquisition. However, it is difficult to determine how well subjects implement these strategies and, if implemented, how much these strategies contribute to overall performance.(More)
We present a new method to measure workload that offers several advantages. First, it uses non-intrusive means: cameras and a mouse. Second, the workload is measured in real-time. Third, the setup is comparably cheap: the cameras and sensors are off-the-shelf components. Fourth, we go beyond measuring performance and demonstrate that just using such(More)
We propose an approach to the cognitive engineering of integrated task environments by the use of simulated cyborgs (simBorgs). SimBorgs combine high-fidelity computational cognitive models with low-fidelity artificial intelligence (AI) based reasoning components. This combination of cognitive modeling with AI enables the creation of intelligent agents,(More)