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11 results for “decision theory”
Canonical Decision Diagrams Modulo Theories - Benchmarking
<p>This archive contains all data and results that were used to benchmark the approach Canonical Decision Diagrams Modulo Theories. The archive contains the following files: 3 subfolders, one for each dataset that was used in the benchmarking process, each one containing a "data" subfolder which contains the problems (in SMT/SMT2 format) and some output folders which contain JSON files describing in detail the results of each run on the problems.</p>
Data from: Contingent tradeoff decisions with feedbacks in cyclical environments: testing alternative theories
<p>This archive contains the model code and input for the simulation experiments published in: Railsback, Harvey, and Ayllón, in press. Contingent tradeoff decisions with feedbacks in cyclical environments: testing alternative theories. Behavioral Ecology. BEHECO-2019-0460.R3. That paper formulates and tests four alternative theories for how animals make tradeoff decisions throughout the circadian light cycle in a population context, with the behavior of each individual affecting the resources available to others. The example application is to stream trout selecting when and where to feed vs. hide, during dawn, day, dusk, and night. These theories are tested against observed patterns reported in the literature. The archive provides separate NetLogo program files for each theory and each simulation experiment. These files allow complete reproduction of the simulation experiments.</p>
Data from: Moving on with foraging theory: incorporating movement decisions into the functional response of a gregarious shorebird
1. Models relating intake rate to food abundance and competitor densities (generalized functional response models) can predict forager distributions and movements between patches, but we lack understanding of how distributions and small-scale movements by the foragers themselves affect intake rates. 2. Using a state-of-the-art approach based on continuous-time Markov chain dynamics, we add realism to classic functional response models by acknowledging that the chances to encounter food and competitors are influenced by movement decisions, and, vice versa, that movement decisions are influenced by these encounters. 3. We used a multi-state modelling framework to construct a stochastic functional response model in which foragers alternate between three behavioural states: searching, handling and moving. 4. Using behavioural observations on a molluscivore migrant shorebird (red knot, Calidris canutus canutus), at its main wintering area (Banc d'Arguin, Mauritania), we estimated transition rates between foraging states as a function of conspecific densities and densities of the two main bivalve prey. 5. Intake rate decreased with conspecific density. This interference effect was not due to decreased searching efficiency, but resulted from time lost to avoidance movements. 6. Red knots showed a strong functional response to one prey (Dosinia isocardia), but a weak response to the other prey (Loripes lucinalis). This corroborates predictions from a recently developed optimal diet model that accounts for the mildly toxic effects due to consuming Loripes. 7. Using model-averaging across the most plausible multi-state models, the fully parameterized functional response model was then used to predict intake rate for an independent dataset on habitat choice by red knot. 8. Comparison of the sites selected by red knots with random sampling sites showed that the birds fed at sites with higher than average Loripes and Dosinia densities, i.e. sites for which we predicted higher than average intake rates. 9. We discuss the limitations of Holling's classical functional response model that ignores movement and the limitations of contemporary movement ecological theory ignoring consumer-resource interactions. With the rapid advancement of technologies to track movements of individual foragers at fine spatial scales, the time seems ripe to integrate descriptive tracking studies with stochastic movement-based functional response models.
DECISION MAKING THEORIES IN BOTH HEALTH RELATED BEHAVIORS AND ENVIRONMENTAL BEHAVIORS
<p>DECISION MAKING THEORIES IN BOTH HEALTH RELATED BEHAVIORS AND ENVIRONMENTAL BEHAVIORS</p>
Data from: Decision making for mitigating wildlife diseases: from theory to practice for an emerging fungal pathogen of amphibians
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Data from: Contingent tradeoff decisions with feedbacks in cyclical environments: testing alternative theories
Open the record for dataset details and reuse information.
Data from: Moving on with foraging theory: incorporating movement decisions into the functional response of a gregarious shorebird
Open the record for dataset details and reuse information.
Data from: Integrating encounter theory with decision analysis to evaluate collision risk and determine optimal protection zones for wildlife
1. Better understanding human-wildlife interactions and their links with management can help improve the design of wildlife protection zones. One important example is the problem of wildlife collisions with vehicles or human-built structures (e.g. power lines, wind farms). In fact, collisions between marine wildlife and watercraft are among the major threats faced by several endangered species of marine mammals. Natural resource managers are therefore interested in finding cost-effective solutions to mitigate these threats. 2. We combined abundance estimators with encounter rate theory to estimate relative lethal collision risk of the Florida manatee (Trichechus manatus latirostris) from watercraft. We first modeled seasonal abundance of watercraft and manatees using a Bayesian analysis of aerial survey count data. We then modeled relative lethal collision risk in space and across seasons. Finally, we applied decision analysis and Linear Integer Programming to determine the optimal design of speed zones in terms of relative risk to manatees and costs to waterway users. We used a Pareto efficient frontier approach to evaluate the performance of alternative zones, which included additional practical considerations (e.g. spatial aggregation of speed zones) in relation to the optimal zone configurations. 3. Under the various relationships for probability of death given strike speed that we considered, the current speed zones reduced the relative lethal collision risk by an average of 51.5% to 70% compared to the scenario in which all speed regulations were removed (i.e. the no-protection scenario). We identified optimal zones and near-optimal zones with additional management considerations that improved upon the current zones in terms of cost or relative risk. 4. Policy Implications: Our analytical framework combines encounter rate theory and decision analysis to quantify the effectiveness of speed zones protecting manatees while accounting for uncertainty. Our approach can be used to optimize the design of protection zones intended to reduce conflicts between human waterborne activity and marine mammals. This framework could be extended to address many other problems of human-wildlife interactions, such as the optimal placement of wind farms to minimize collisions with wildlife or the optimal allocation of ranger effort to mitigate poaching threats.
Data from: Integrating encounter theory with decision analysis to evaluate collision risk and determine optimal protection zones for wildlife
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End-of-life Decision-making Among Young Patients With Advanced Cancer: a Grounded Theory Approach
ClinicalTrials.gov study NCT06551831. IPD Sharing: NO. Countries: 1. Publications: 0.
Bridging the Gap Between Theory and Practice: Evaluating Embedded Micro-Scenarios in Simulation on Academic Motivation and Clinical Decision-Making Among Nursing Students-A Randomized Controlled Trial
ClinicalTrials.gov study NCT07184112. IPD Sharing: NO. Countries: 1. Publications: 0.
ScienceDex guides
Understand access before you commit
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.