Decision-making and planning of computer generated forces

2012 ◽  
Author(s):  
Shaobin Sun ◽  
Xuehua Lin ◽  
Jun Pan ◽  
Yingchun Zhou
Keyword(s):  
Decision Making ◽  
Computer Generated Forces

Training and Assessing Complex Decision-Making in a Virtual Environment

2002 ◽  
Vol 94 (3) ◽  
pp. 871-882 ◽  
Author(s):  
Robert J. Pleban ◽  
Michael D. Matthews ◽  
Margaret S. Salter ◽  
David E. Eakin
Keyword(s):  
Decision Making ◽  
Virtual Environment ◽  
Lessons Learned ◽  
Urban Setting ◽  
Training Procedure ◽  
Small Unit ◽  
Subjective Assessments ◽  
Computer Generated Forces ◽  
Complex Decision Making ◽  
Complex Decision

The current report describes a procedure for training and assessing complex decision-making in a virtual environment. Focusing on small unit leaders, 7 experienced and 7 inexperienced Army platoon leaders performed missions in a combat simulator, where they were required to direct the activities of 3 subordinate leaders and computer-generated forces in 4 different operations in a virtual urban setting. Objective and subjective assessments of the training value of the simulations showed that both experienced an inexperienced platoon leaders improved their decision-making across the four missions, and both groups rated this “virtual environment” training procedure as useful and positive. Lessons learned and implications for designing similar training protocols for other domains are discussed.

Discarding optimality: Throwing out the baby with the bathwater?

2018 ◽  
Vol 41 ◽  
Author(s):  
Patrick Simen ◽  
Fuat Balcı
Keyword(s):  
Decision Making ◽  
Perceptual Decision Making ◽  
Reward Rate ◽  
Perceptual Decision ◽  
Standard Observer ◽  
Rate Maximization ◽  
Reward Rate Maximization ◽  
Descriptive Standard ◽  
Observer Model

AbstractRahnev & Denison (R&D) argue against normative theories and in favor of a more descriptive “standard observer model” of perceptual decision making. We agree with the authors in many respects, but we argue that optimality (specifically, reward-rate maximization) has proved demonstrably useful as a hypothesis, contrary to the authors’ claims.

LPCD framework: Analytical tool or psychological model?

2018 ◽  
Vol 41 ◽  
Author(s):  
David Danks
Keyword(s):  
Decision Making ◽  
Analytical Tool ◽  
Mathematical Framework ◽  
Bayesian Decision ◽  
Perceptual Decision Making ◽  
Psychological Model ◽  
Psychological Reality ◽  
Psychological Theories ◽  
Target Article ◽  
Bayesian Decision Making

AbstractThe target article uses a mathematical framework derived from Bayesian decision making to demonstrate suboptimal decision making but then attributes psychological reality to the framework components. Rahnev & Denison's (R&D) positive proposal thus risks ignoring plausible psychological theories that could implement complex perceptual decision making. We must be careful not to slide from success with an analytical tool to the reality of the tool components.

Elaborating the role of reflection and individual differences in the study of folk-economic beliefs

2018 ◽  
Vol 41 ◽  
Author(s):  
Kevin Arceneaux
Keyword(s):  
Decision Making ◽  
Individual Differences ◽  
Cognitive Processes ◽  
Evolutionary History ◽  
Behavioral Responses ◽  
History Of ◽  
Economic Beliefs

AbstractIntuitions guide decision-making, and looking to the evolutionary history of humans illuminates why some behavioral responses are more intuitive than others. Yet a place remains for cognitive processes to second-guess intuitive responses – that is, to be reflective – and individual differences abound in automatic, intuitive processing as well.

The primacy of conscious decision making – ERRATUM

2014 ◽  
Vol 38 (01) ◽  
pp. 46
Author(s):  
David R. Shanks ◽  
Ben R. Newell
Keyword(s):  
Decision Making ◽  
Conscious Decision

The primacy of conscious decision making – RETRACTION

2014 ◽  
Vol 38 (01) ◽  
pp. 48
Author(s):  
David R. Shanks ◽  
Ben R. Newell
Keyword(s):  
Decision Making ◽  
Conscious Decision

Abstraction: An alternative neurocognitive account of recognition, prediction, and decision making

2020 ◽  
Vol 43 ◽  
Author(s):  
Valerie F. Reyna ◽  
David A. Broniatowski
Keyword(s):  
Decision Making ◽  
Software Engineering ◽  
Systems Engineering ◽  
Evidence Based ◽  
Extensive Literature ◽  
Trace Theory ◽  
Fuzzy Trace Theory ◽  
Abstract Representations ◽  
Technical Systems

Abstract Gilead et al. offer a thoughtful and much-needed treatment of abstraction. However, it fails to build on an extensive literature on abstraction, representational diversity, neurocognition, and psychopathology that provides important constraints and alternative evidence-based conceptions. We draw on conceptions in software engineering, socio-technical systems engineering, and a neurocognitive theory with abstract representations of gist at its core, fuzzy-trace theory.

The Relationship Between Hearing Loss Self-Management and Hearing Aid Benefit and Satisfaction

2019 ◽  
Vol 28 (2) ◽  
pp. 274-284 ◽  
Author(s):  
Elizabeth Convery ◽  
Gitte Keidser ◽  
Louise Hickson ◽  
Carly Meyer
Keyword(s):  
Decision Making ◽  
Hearing Loss ◽  
Hearing Aids ◽  
Clinical Decision Making ◽  
Hearing Aid ◽  
Well Being ◽  
Self Report ◽  
Self Management ◽  
Hearing Aid Benefit ◽  
The Relationship

Purpose Hearing loss self-management refers to the knowledge and skills people use to manage the effects of hearing loss on all aspects of their daily lives. The purpose of this study was to investigate the relationship between self-reported hearing loss self-management and hearing aid benefit and satisfaction. Method Thirty-seven adults with hearing loss, all of whom were current users of bilateral hearing aids, participated in this observational study. The participants completed self-report inventories probing their hearing loss self-management and hearing aid benefit and satisfaction. Correlation analysis was used to investigate the relationship between individual domains of hearing loss self-management and hearing aid benefit and satisfaction. Results Participants who reported better self-management of the effects of their hearing loss on their emotional well-being and social participation were more likely to report less aided listening difficulty in noisy and reverberant environments and greater satisfaction with the effect of their hearing aids on their self-image. Participants who reported better self-management in the areas of adhering to treatment, participating in shared decision making, accessing services and resources, attending appointments, and monitoring for changes in their hearing and functional status were more likely to report greater satisfaction with the sound quality and performance of their hearing aids. Conclusion Study findings highlight the potential for using information about a patient's hearing loss self-management in different domains as part of clinical decision making and management planning.

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