Computer modeling of human decision making

Models of human decision making are reviewed. Models which treat just the cognitive aspects of human behavior are included as well as models which include motivation. Both models which have associated computer programs, and those that do not, are considered. Since flow diagrams, that assist in constructing computer simulation of such models, were not generally available, such diagrams were constructed and are presented. The result provides a rich source of information, which can aid in construction of more realistic future simulations of human decision making

Suppressing visual feedback in written composition: Effects on processing demands and coordination of the writing processes

The goal of this experiment was to investigate the role of visual feedback during written composition. Effects of suppression of visual feedback were analysed both on processing demands and on on-line coordination of low-level execution processes and of high-level conceptual and linguistic processes. Writers composed a text and copied it either with or without visual feedback. Processing demands of the writing processes were evaluated with reaction times to secondary auditory probes that were analysed according to whether participants were handwriting (in a composing and a copying tasks) or engaged in high level processes (when pausing in a composing task). Suppression of visual feedback increased reaction times interference (secondary reaction time minus baseline reaction time) during handwriting in the copying task and not during pauses in the composing task. This suggests that suppression of visual feedback affected processing demands of only execution processes and not those of high-level conceptual and linguistic processes. This is confirmed by analysis of quality of the texts produced by participants that were little, if any, affected by the suppression of visual feedback. Results also indicate that the increase in processing demands of execution related to suppression of visual feedback affected on-line coordination of the writing processes. Indeed, when visual feedback was suppressed, reaction time interferences associated to handwriting were not reliable different in the copying task and in the composing task but were significantly different in the composition task, RT interference associated to handwriting being lower in the copying task than in the composition task. When visual feedback was suppressed, writers activated step-by-step execution processes and high-level writing processes, whereas they concurrently activated these writing processes when composing with visual feedback

Why are we not flooded by involuntary autobiographical memories? Few cues are more effective than many

Recent research on involuntary autobiographical memories (IAMs) has shown that these memories can be elicited and studied in the laboratory under controlled conditions. Employing a modified version of a vigilance task developed by Schlagman and Kvavilashvili (Mem Cogn 36:920–932, 2008) to elicit IAMs, we investigated the effects of varying the frequency of external cues on the number of IAMs reported. During the vigilance task, participants had to detect an occasional target stimulus (vertical lines) in a constant stream of non-target stimuli (horizontal lines). Participants had to interrupt the task whenever they became aware of any task-unrelated mental contents and to report them. In addition to line patterns, participants were exposed to verbal cues and their frequency was experimentally manipulated in three conditions (frequent cues vs. infrequent cues vs. infrequent cues plus arithmetic operations). We found that, compared to infrequent cues, both conditions with frequent cues and infrequent cues plus arithmetic operations decreased the number of IAMs reported. The comparison between the three experimental conditions suggests that this reduction was due to the greater cognitive load in conditions of frequent cues and infrequent cue plus arithmetic operations. Possible mechanisms involved in this effect and their implications for research on IAMs are discussed

A situated cognition perspective on presence

During interaction with computer-based 3-D simulations like virtual reality, users may experience a sense of involvement called presence. Presence is commonly defined as the subjective feeling of "being there". We discuss the state of the art in this inno vative research area and introduce a situated cognition perspective on presence. We argue that presence depends on the proper integration of aspects relevant to an agent's movement and perception, to her actions, and to her conception of the overall situ a tion in which she finds herself, as well as on how these aspects mesh with the possibilities for action afforded in the interaction with the artifact. We also aim at showing that studies of presence offer a test-bed for different theories of situated co gnition.

Movement, Action, and Situation: Presence in Virtual Environments

Presence is commonly defined as the subjective feeling of "being there". It has been mainly conceived of as deriving from immersion, interaction, and social and narrative involvement with suitable technology. We argue that presence depends on a suitable integration of aspects relevant to an agent's movement and perception, to her actions, and to her conception of the overall situation in which she finds herself, as well as on how these aspects mesh with the possibilities for action afforded in the interaction with the virtual environment

The electrocortical correlates of fluctuating states of attention during vigilance tasks

This study investigated the electrocortical correlates of attention. Sixteen subjects (seven females, nine males) engaged in a forty-minute target detection vigilance task. Task-irrelevant probe tones were presented every 2-4 seconds. While performing the vigilance task, the subjects were asked to press a button if they were daydreaming (i.e. having a task unrelated thought or TUT). Continuous electroencephalograms (EEG's) and event-related potentials (ERP's) were recorded from the subjects during the entire task. The continuous EEG data were analyzed for differences in absolute power throughout the task as well as before and after the subjects indicated that they were daydreaming (TUT response). ERP's elicited by task-irrelevant probe tones were analyzed in the same manner. The results indicated performance decrements as reflected by increased RT to correct detections, and decreased number of hits. Further, as the task progressed, the number of reports of daydreaming increased. The analysis of the EEG data indicated a significant difference in the absolute power of the different frequency bands across periods. The greatest difference was observed at the posterior parietal electrode sites. In addition, when the EEG data was converted into band ratios (beta/alpha and beta/alpha+theta), the pre-TUT conditions were found to be significantly different than the post-TUT conditions in the posterior sites. The ERP components (N1, N2, and P2) were not significantly different before and after a TUT response or across periods. However, the ERP's across periods exhibited amplitudes that were similar to those found in previous studies of vigilance and ERP's

Finding identity in memories

What are the ways in which we form and build our identities and habits in both physical and digital spaces? How can our different uses of the digital expression which evolved from analog forms reveal traits and memories that we have forgotten or overlooked? The way I define my identity through the analog media I collect correlates with the quality of the memories within my current schema, knowledge structures that represent typical instances of categories. We interact with an infinity of objects from birth to death. Our collection of objects resonates more and more with memory and nostalgia as the years pass. Personal belongings express aspects of our identity, our values and our choices. As I dug through my collections of memories, mementos and memorabilia from childhood to college, I found memories of interpersonal connections solidified into a collection of cherished objects that have been with me since Kindergarten. This retrospection allowed me to maintain my self image, my desired identity over time, and to avoid conflicting narratives about who I am. The collection of physical materials creates another layer of retrospective interaction with myself in the present, with people, and with myself in the past. I created distorted memories to address the absence of a clear history of past interactions, which raised my appreciation of the objects as I used them to fill gaps in my memories with imagination. In digital space, my habit of collection continues, but my relationship to objects and memories has changed. My collection of “flat” media, such as photos, files from Google Drive, and text messages, has changed how I view my identity, fixing and changing the memories associated with these files, and blocking both other memories, as well as the imaginative “filling in” process. The process of forming my identity changed from using my imagination to fill gaps left by physical mementos, to relying on selectively chosen, immutable images. In this way, the way I have collected memories has changed, and these changes have directly affected how I form my identity. My artistic practice is to explore the formation of identity through the materialization and objectification of my memories in both analog and digital formats. When my identity is shaped by the flood of digital water, it creates conflicting narratives about who I am. I want to be the master of the digital brush to take ownership, and create my own narratives, rather than letting those digital brushes shape my identity for me. Therefore, I investigated the various expressions of identity in emerging platforms that originated from my memories in the physical world by observing the patterns of my own behaviors, and explored new possibilities for interacting with technology by carrying one’s desired identity into both physical and digital spaces

Driver Distraction Identification with an Ensemble of Convolutional Neural Networks

The World Health Organization (WHO) reported 1.25 million deaths yearly due to road traffic accidents worldwide and the number has been continuously increasing over the last few years. Nearly fifth of these accidents are caused by distracted drivers. Existing work of distracted driver detection is concerned with a small set of distractions (mostly, cell phone usage). Unreliable ad-hoc methods are often used.In this paper, we present the first publicly available dataset for driver distraction identification with more distraction postures than existing alternatives. In addition, we propose a reliable deep learning-based solution that achieves a 90% accuracy. The system consists of a genetically-weighted ensemble of convolutional neural networks, we show that a weighted ensemble of classifiers using a genetic algorithm yields in a better classification confidence. We also study the effect of different visual elements in distraction detection by means of face and hand localizations, and skin segmentation. Finally, we present a thinned version of our ensemble that could achieve 84.64% classification accuracy and operate in a real-time environment.Comment: arXiv admin note: substantial text overlap with arXiv:1706.0949