Modeling Cognitive Parsimony with a Demand Selection Task

The law of less work (Hull, 1943) is our natural tendency given two alternatives with equal incentives to pick the less demanding one. This notion also appears in the field of judgment and decision making (Gigerenzer & Goldstein, 1996; Tversky & Kahneman, 1974), it is referred to as internal cost of effort. Cognitive parsimony is our tendency to favour low-effort strategies that help us to decide faster and simple strategies to approach a complex problem. An experimental paradigm for this phenomenon has been developed by Kool, McGuire, Rosen, & Botvinick (2010) and referred to as the demand selection task. In this poster, we present a model of this task developed in the ACT-R architecture (Anderson, 2007), which offers an hypothesis as to which cognitive mechanisms might participate in this phenomenon

Automated Update Tools To Augment the Wisdom of Crowds in Geopolitical Forecasting

Despite the importance of predictive judgments, individual human forecasts are frequently less accurate than those of even simple prediction algorithms. At the same time, not all forecasts are amenable to algorithmic prediction. Here, we describe the evaluation of an automated prediction tool that enabled participants to create simple rules that monitored relevant indicators (e.g., commodity prices) to automatically update forecasts. We examined these rules in both a pool of previous participants in a geopolitical forecasting tournament (Study 1) and a naïve sample recruited from Mechanical Turk (Study 2). Across the two studies, we found that automated updates tended to improve forecast accuracy relative to initial forecasts and were comparable to manual updates. Additionally, making rules improved the accuracy of manual updates. Crowd forecasts likewise benefitted from rule-based updates. However, when presented with the choice of whether to accept, reject or adjust an automatic forecast update, participants showed little ability to discriminate between automated updates that were harmful versus beneficial to forecast accuracy. Simple prospective rule-based tools are thus able to improve forecast accuracy by offering accurate and efficient updates, but ensuring forecasters make use of tools remains a challenge

Emotion in the Common Model of Cognition

Emotions play an important role in human cognition and therefore need to be present in the Common Model of Cognition. In this paper, the emotion working group focuses on functional aspects of emotions and describes what we believe are the points of interactions with the Common Model of Cognition. The present paper should not be viewed as a consensus of the group but rather as a first attempt to extract common and divergent aspects of different models of emotions and how they relate to the Common Model of Cognition

Emotion in the Common Model of Cognition

Emotions play an important role in human cognition and therefore need to be present in the Common Model of Cognition. In this paper, the emotion working group focuses on functional aspects of emotions and describes what we believe are the points of interactions with the Common Model of Cognition. The present paper should not be viewed as a consensus of the group but rather as a first attempt to extract common and divergent aspects of different models of emotions and how they relate to the Common Model of Cognition

IONS-VIP: A Cognitive Model for Navigating the Web Via Screen Readers

This paper presents a cognitive perspective on the problem of using the Internet via screen readers. An empirical study shows similarities and dissimilarities between using the Internet via screen readers and via the standard graphical screen. In particular, spatial cognition is an important determinant of web task performance even in the absence of any visual cues. Backtracking behavior has a higher cost and impacts performance in a more negative way when using the Internet via screen readers as compared to the standard use. Selective reading can be used as an addition to the existing functionality of screen readers but more research is needed to prove the utility of such support mechanism. Computational cognitive modeling can be used in conceiving, testing and implementing cognitively informed support functionality in screen readers

Neural Substrates of Inhibitory Control: A Review and Critique

Inhibitory control is difficult to study in behavioral experiments because of its nature; a successful inhibition act does not manifest overtly, thus cannot be directly observed and measured (Kana, Keller, Minshew & Just, 2007). Some influential theorists have called the very existence of cognitive inhibition into question (MacLeod, 2007a). This is a case where brain-imaging research holds the promise to be able to shed light into the covert nature of inhibition, with potentially immeasurable impact on understanding and ameliorating conditions such as ADHD, addiction, and frontal lobe injuries. A critical review of the literature shows that inhibitory control is subserved by a network of brain regions including as key components the inferior frontal cortex, the pre-supplementary motor area, and the sub-thalamic nucleus. It is argued that inhibitory control makes use of basic cognitive processes such as internalized speech. A common inhibitory mechanism for motor, speech and thought acts is proposed. Practical applications of research on inhibitory control are discussed such as brain plasticity exercises and electrical brain stimulation

How Attentional Blink Facilitates Multitasking

Multitasking is a required skill for complex and dynamic activities such as driving a car and piloting an airplane. Previous research in cognitive modeling has suggested that top-down control improves multitasking ability (Taatgen, 2005). An empirical study has been conducted to investigate how a basic neuro-cognitive effect (attentional blink) makes top-down control possible and improves multitasking performance

How Attentional Blink Facilitates Multitasking

Multitasking is a required skill for complex and dynamic activities such as driving a car and piloting an airplane. Previous research in cognitive modeling has suggested that top-down control improves multitasking ability (Taatgen, 2005). An empirical study has been conducted to investigate how a basic neuro-cognitive effect (attentional blink) makes top-down control possible and improves multitasking performance