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1,032 results for “Decision making”
Experiments of Multiple Decision Making in CDCL SAT Solvers
<p>With these experiments (submission), we show that Multiple Decision Making (MDM) has a positive impact on CDCL, for many different SAT application problems when alternating between different decision queues and frequently running the WalkSAT strategy. Overall, MDM allowed the CDCL search to solve extra 10 formulas in the SAT competition 2020 benchmark set, and achieves a minimum PAR-2 score of 3,473 compared to the state of the art solver Kissat.</p>
What Influences Algorithmic Decision-Making? A Systematic Literature Review on Algorithm Aversion
<p>Abstract</p> <p> </p> <p>With the continuing application of artificial intelligence (AI) technologies into decision-making, algorithmic decision-making is becoming more efficient, even often outperforming human counterpart. Despite this superior performance, people often consciously or unconsciously display reluctance to rely on algorithms, a phenomenon known as algorithm aversion. Viewed as a behavioral anomaly, algorithm aversion has recently attracted much scholarly attention. With a view to synthesize the findings of this literature, we systematically review 80 empirical studies identified through searching in seven academic databases and performing citation chaining. We map the emergent themes following grounded theory and categorize the influencing factors of algorithm aversion under four main themes: algorithm, individual, task, and high-level. Our analysis reveals that although algorithm and individual factors have been investigated extensively, very little effort has been given to explore the task and high-level factors. We contribute to algorithm aversion literature by proposing a comprehensive framework, highlighting open issues in existing studies, and outlining several research avenues that could be handled in future research. Implications for research and practitioners about the findings of the study are discussed.</p>
SLR on Algorithmic Decision Making
<p>Abstract</p> <p> </p> <p>With the continuing application of artificial intelligence (AI) technologies into decision-making, algorithmic decision-making is becoming more efficient, even often outperforming human counterpart. Despite this superior performance, people often consciously or unconsciously display reluctance to rely on algorithms, a phenomenon known as algorithm aversion. Viewed as a behavioral anomaly, algorithm aversion has recently attracted much scholarly attention. With a view to synthesize the findings of this literature, we systematically review 80 empirical studies identified through searching in seven academic databases and performing citation chaining. We map the emergent themes following grounded theory and categorize the influencing factors of algorithm aversion under four main themes: algorithm, individual, task, and high-level. Our analysis reveals that although algorithm and individual factors have been investigated extensively, very little effort has been given to explore the task and high-level factors. We contribute to algorithm aversion literature by proposing a comprehensive framework, highlighting open issues in existing studies, and outlining several research avenues that could be handled in future research. Implications for research and practitioners about the findings of the study are discussed.</p> <p> </p> <p> </p>
Data: Promoting informed decision making about Maternal Pertussis Vaccination in the Netherlands
<p>We used Intervention Mapping to develop and test two interventions promoting informed decision making about Maternal Pertussis Vaccination. Anonymised focus-group/interview data, trial data in which one of the interventions is tested, and data from an experiment testing strategies to reduce negative affect in the decision making process about MPV are included. Data descriptions can be found in the accompanied files. Results are yet to be published by the authors.</p>
Raw data for Peters et al., ENeuro (2020): Dopamine and risky decision-making in gambling disorder
<p>Raw behavioral data for Peters et al. (2020), eNeuro: Dopamine and risky decision-making in gambling disorder. The data structure (Matlab matrix) is explained in the Readme.txt</p>
Dopaminergic modulation of the exploration/exploitation trade-off in human decision-making
<p>raw choice data of the four-armed bandit task</p> <p>1. fMRI study (31 participants, 3 drug conditions (placebo, L-dopa, haloperidol) )</p> <p>2. pilot study (16 participants)</p>
Decision-making across four cancer multidisciplinary teams
<p>Observational data of four cancer teams measuring quality of decision-making processes.</p>
EEG-based approach for predicting varied human cognitive decision-making in driving
<p>These data are part of the data sample of the paper "EEG-based approach for predicting varied human cognitive decision-making in driving". For use by editors and reviewers. This includes one compressed files: 'RAW Data.zip'. 'RAW Data.zip' includes EEG Data and driving behavior data as well as code for extracting features and training individual models. A detailed description can be found in 'Read_Me.txt'. </p>
EEG-based approach for predicting varied human cognitive decision-making in driving
<p>These data are part of the data sample of the paper "EEG-based approach for predicting varied human cognitive decision-making in driving". For use by Nature Communications editors. This includes one compressed files: 'RAW Data.zip'. 'RAW Data.zip' includes EEG Data and driving behavior data as well as code for extracting features and training individual models. A detailed description can be found in 'Read_Me.txt'. </p>
Investor Decision making and Founder Social Capital
<p>Data set with analysis of choice models that best describe investor decisions based on founder human and social capital </p>
Moral decision making in healthcare and medical professions during the COVID-19 pandemic
<p>The Data supports the findings of the article with the same name.</p>
Worst Case for high stakes surgical decision making conversations
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ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.