Search results for "decision making"

showing 10 items of 492 documents

Manipulating Individual Decisions and Environmental Conditions Reveal Individual Quality in Decision-Making and Non-Lethal Costs of Predation Risk

2012

Received: July 6, 2012; Accepted: November 13, 2012; Published: December 13, 2012

0106 biological sciencesAnimal breedingEcophysiology01 natural sciencesNesting BehaviorPredationSongbirdsBehavioral EcologyOrnithologyMolecular Cell BiologyCellular Stress ResponsesAnimal Managementmedia_common0303 health sciencesMultidisciplinaryEcologyAnimal BehaviorEcologyReproductionPhysiological conditionQRCommunity EcologyHabitatMedicineFemaleResearch ArticleOffspringSciencemedia_common.quotation_subjectDecision MakingEnvironmentBiology010603 evolutionary biologyBirds03 medical and health sciencesAnimalsQuality (business)BiologyCommunity StructureEcosystemSelection (genetic algorithm)030304 developmental biologyEvolutionary BiologyReproductive successHawksSpecies InteractionsEvolutionary EcologyPredatory Behaviorta1181Veterinary ScienceZoologyPLoS One
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Simple learning rules to cope with changing environments

2008

10 pages; International audience; We consider an agent that must choose repeatedly among several actions. Each action has a certain probability of giving the agent an energy reward, and costs may be associated with switching between actions. The agent does not know which action has the highest reward probability, and the probabilities change randomly over time. We study two learning rules that have been widely used to model decision-making processes in animals-one deterministic and the other stochastic. In particular, we examine the influence of the rules' 'learning rate' on the agent's energy gain. We compare the performance of each rule with the best performance attainable when the agent …

0106 biological sciencesError-driven learningExploitComputer scienceEnergy (esotericism)Biomedical EngineeringBiophysicsBioengineeringanimal behavior010603 evolutionary biology01 natural sciencesBiochemistryMulti-armed banditModels Biologicaldecision makingBiomaterials03 medical and health sciences[ INFO.INFO-BI ] Computer Science [cs]/Bioinformatics [q-bio.QM][ SDV.EE.IEO ] Life Sciences [q-bio]/Ecology environment/SymbiosisAnimalsLearningComputer Simulation[ SDV.BIBS ] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]multi-armed banditEcosystem030304 developmental biologySimple (philosophy)0303 health sciences[ SDE.BE ] Environmental Sciences/Biodiversity and Ecologybusiness.industrydynamic environmentslearning rulesdecision-making[SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]Unlimited periodRange (mathematics)Action (philosophy)Artificial intelligence[SDE.BE]Environmental Sciences/Biodiversity and Ecology[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]businessBiotechnologyResearch Article[SDV.EE.IEO]Life Sciences [q-bio]/Ecology environment/Symbiosis
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Guidelines for risk management in forest planning – what is risk and when is risk management useful?

2018

Managing forest resources occurs under various sources of uncertainty. Depending on the management problem, this uncertainty may have a substantial impact on the quality of the solution. As our knowledge on the sources and magnitude of uncertainty improves, integrating this knowledge into the development of management plans becomes increasingly useful, as additional information can improve the decision-making process. This adjustment requires a fundamental shift in how planning problems are viewed: instead of interpreting risk management as a technique needed only for addressing problems with natural hazards, risk management should be an integral part of most planning problems. Managing ri…

0106 biological sciencesForest planning010504 meteorology & atmospheric sciencesmedia_common.quotation_subjectpäätöksentekoriskienhallintaValue engineering01 natural sciencesconditional value at riskadaptive planningAdaptive planningRisksQuality (business)Environmental planningRisk managementriskit0105 earth and related environmental sciencesmedia_commonriskGlobal and Planetary ChangeEcologyEconomic and social effectsbusiness.industryForestrymetsäsuunnitteluepävarmuusExpected shortfallForest resourceRisk managementmetsänhoitobusinessDecision making010606 plant biology & botany
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Why do house-hunting ants recruit in both directions?

2007

8 pages; International audience; To perform tasks, organisms often use multiple procedures. Explaining the breadth of such behavioural repertoires is not always straightforward. During house hunting, colonies of Temnothorax albipennis ants use a range of behaviours to organise their emigrations. In particular, the ants use tandem running to recruit na? ants to potential nest sites. Initially, they use forward tandem runs (FTRs) in which one leader takes a single follower along the route from the old nest to the new one. Later, they use reverse tandem runs (RTRs) in the opposite direction. Tandem runs are used to teach active ants the route between the nests, so that they can be involved qui…

0106 biological sciencesMESH: Decision MakingOperations researchTemnothorax albipennisMESH : Social BehaviorTandem runningSocial insectsMESH : Behavior Animal01 natural sciencesNesting BehaviorNestMESH : EcosystemMESH: Behavior Animal[ SDV.EE.IEO ] Life Sciences [q-bio]/Ecology environment/SymbiosisMESH: AnimalsMESH: EcosystemMESH: Nesting BehaviorRecruitment methodsMESH: Models Theoretical0303 health sciencesBehavior AnimalbiologyEcologyGeneral MedicineMESH : AntsCollective behaviourMESH: Social BehaviorTandem runningMESH: Population DensityDecision MakingMESH: AntsMESH : Nesting Behavior010603 evolutionary biology03 medical and health sciencesAnimalsTemnothorax albipennisMESH : Population DensitySocial BehaviorSet (psychology)EcosystemEcology Evolution Behavior and Systematics030304 developmental biologyPopulation DensityOriginal PaperAntsMESH : Models TheoreticalModels TheoreticalRecruitment methodsbiology.organism_classificationMESH : Decision MakingMESH : Animals[SDV.EE.IEO]Life Sciences [q-bio]/Ecology environment/Symbiosis
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Risk of predation makes foragers less choosy about their food.

2017

18 pages; International audience; Animals foraging in the wild have to balance speed of decision making and accuracy of assessment of a food item's quality. If resource quality is important for maximizing fitness, then the duration of decision making may be in conflict with other crucial and time consuming tasks, such as anti-predator behaviours or competition monitoring. Individuals facing the risk of predation and/or competition should adjust the duration of decision making and, as a consequence, their level of choosiness for resources. When exposed to predation, the forager could either maintain its level of choosiness for food items but accept a reduction in the amount of food items con…

0106 biological sciencesPhysiologylcsh:MedicinePredationSocial SciencesKaplan-Meier EstimateChoice Behavior01 natural sciencesPredationCognitionMathematical and Statistical TechniquesBeetlesMedicine and Health Sciences[ SDV.EE.IEO ] Life Sciences [q-bio]/Ecology environment/SymbiosisPsychologyForagingDecision-makinglcsh:Sciencemedia_common2. Zero hungerMultidisciplinaryEcologyAnimal BehaviorEcology05 social sciencesEukaryotaPlantsTrophic InteractionsInsectsCommunity EcologyPhysical SciencesSeedsStatistics (Mathematics)Research ArticleRiskOpportunity costArthropodaMovementmedia_common.quotation_subjectDecision MakingForagingBiologyResearch and Analysis Methods010603 evolutionary biologyIntraspecific competitionCompetition (biology)Food PreferencesAnimals0501 psychology and cognitive sciencesQuality (business)050102 behavioral science & comparative psychologyStatistical MethodsBehavior[ SDE.BE ] Environmental Sciences/Biodiversity and Ecologylcsh:REcology and Environmental SciencesCognitive PsychologyFood ConsumptionOrganismsBiology and Life SciencesInterspecific competitionInvertebratesFoodPredatory BehaviorCognitive Sciencelcsh:QWeeds[SDE.BE]Environmental Sciences/Biodiversity and EcologyPhysiological ProcessesZoologyMathematicsNeuroscienceGeneralized Linear ModelDemography[SDV.EE.IEO]Life Sciences [q-bio]/Ecology environment/Symbiosis
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Large differences in catch per unit of effort between two minnow trap models

2013

Background: Little is known about variation in catch per unit of effort (CPUE) in stickleback fisheries, or the factors explaining this variation. We investigated how nine-spined stickleback (Pungitius pungitius) CPUE was influenced by trap model by comparing the CPUEs of two very similar minnow trap models fished side-by-side in a paired experimental design. Results: The galvanized trap type (mean CPUE = 1.31 fish h–1) out-fished the black trap type (mean CPUE = 0.20 fish h–1) consistently, and yielded on average 81% more fish. Conclusions: The results demonstrate that small differences in trap appearance can have large impacts on CPUE. This has implications for studies designed to investi…

0106 biological sciencesputkimertaPungitius pungitiusDecision MakingcpueFisheriesfunnel trapColor010603 evolutionary biology01 natural sciencesGeneral Biochemistry Genetics and Molecular BiologycatchabilityPungitiusAbundance (ecology)biology.animalpyydystettävyysyksikkösaalisAnimalspiikkikalaCatchability14. Life underwaterFunnel trapEcosystemMedicine(all)pyydysBehavior AnimalbiologyBiochemistry Genetics and Molecular Biology(all)stickleback010604 marine biology & hydrobiologySticklebackEquipment DesignGeneral MedicineSticklebackTrap (plumbing)Minnowbiology.organism_classificationSmegmamorphaTrapFisherykalastuskalatalousFishery1181 Ecology evolutionary biologyCPUEFish <Actinopterygii>trapResearch Article
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Bio-inspired evolutionary dynamics on complex networks under uncertain cross-inhibitory signals

2019

Given a large population of agents, each agent has three possiblechoices between option 1 or 2 or no option. The two options are equally favorable and the population has to reach consensus on one of the two options quickly and in a distributed way. The more popular an option is, the more likely it is to be chosen by uncommitted agents. Agents committed to one option can be attracted by those committed to the other option through a cross-inhibitory signal. This model originates in the context of honeybee swarms, and we generalize it to duopolistic competition and opinion dynamics. The contributions of this work include (i) the formulation of a model to explain the behavioral traits of the ho…

0209 industrial biotechnologyMathematical optimizationCollective behaviorAsymptotic stabilityComputer sciencePopulationContext (language use)02 engineering and technologyMachine learningcomputer.software_genreNetwork topologyCompetition (economics)020901 industrial engineering & automationNonlinear systems0202 electrical engineering electronic engineering information engineeringElectrical and Electronic EngineeringEvolutionary dynamicseducationAbsolute stabilityeducation.field_of_studybusiness.industry020208 electrical & electronic engineeringAgentsDeadlock (game theory)Complex networkNetwork topologiesControl and Systems EngineeringArtificial intelligencebusinessDecision makingcomputerAutomatica
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DESDEO: The Modular and Open Source Framework for Interactive Multiobjective Optimization

2021

Interactive multiobjective optimization methods incorporate preferences from a human decision maker in the optimization process iteratively. This allows the decision maker to focus on a subset of solutions, learn about the underlying trade-offs among the conflicting objective functions in the problem and adjust preferences during the solution process. Incorporating preference information allows computing only solutions that are interesting to the decision maker, decreasing computation time significantly. Thus, interactive methods have many strengths making them viable for various applications. However, there is a lack of existing software frameworks to apply and experiment with interactive …

0209 industrial biotechnologylineaarinen optimointiPareto optimizationGeneral Computer Sciencemulti-criteria decision makingComputer sciencepäätöksentekoevoluutiolaskenta02 engineering and technologyData-driven multiobjective optimizationcomputer.software_genrenonlinear optimizationMulti-objective optimizationData modelingopen source softwareavoin lähdekoodi020901 industrial engineering & automationSoftwareoptimointi0202 electrical engineering electronic engineering information engineeringGeneral Materials ScienceUse casecomputer.programming_languageGraphical user interfacepareto-tehokkuusbusiness.industryGeneral Engineeringinteractive methodsModular designPython (programming language)monitavoiteoptimointiTK1-9971Software frameworkdata-driven multiobjective optimizationevolutionary computation020201 artificial intelligence & image processingElectrical engineering. Electronics. Nuclear engineeringbusinessSoftware engineeringcomputerIEEE Access
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Making water smart

2020

International audience

021110 strategic defence & security studiesEnvironmental Engineering[SDE.IE]Environmental Sciences/Environmental EngineeringDecision Making0211 other engineering and technologiesWaterEnvironmental science02 engineering and technology010501 environmental sciences01 natural sciencesComputingMilieux_MISCELLANEOUS0105 earth and related environmental sciencesWater Science and TechnologyWater Science and Technology
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Associations between neuropsychological performance and appetite-regulating hormones in anorexia nervosa and healthy controls: Ghrelin's putative rol…

2019

Anorexia nervosa (AN) is a severe eating disorder accompanied by alterations in endocrinological circuits and deficits in neuropsychological performance. In this study, a series of appetite-regulating hormones (ghrelin, leptin, cholecystokinin, PYY, adiponectin, and visfatin) were measured under fasting conditions in female patients with AN and female healthy controls. All of the participants also underwent a battery of neuropsychological assessment [namely the Iowa Gambling Task (IGT), the Wisconsin Card Sorting Test (WCST), and the Stroop Color and Word Test (SCWT)]. As the main finding, we found that higher ghrelin levels predict better performance in the IGT. Ghrelin may be a putative m…

0301 basic medicineAdultmedicine.medical_specialtyAnorexia Nervosamedia_common.quotation_subjectDecision MakingAppetite030209 endocrinology & metabolismNeuropsychological TestsBiochemistryModels BiologicalCohort Studies03 medical and health sciencesYoung Adult0302 clinical medicineEndocrinologyWisconsin Card Sorting TestInternal medicineAppetite regulationmedicineHumansNeuropsychological assessmentMolecular Biologymedia_commonmedicine.diagnostic_testbusiness.industryLeptindigestive oral and skin physiologyAppetiteAnorexia nervosaIowa gambling taskNeuropsychological performanceGhrelin030104 developmental biologyEndocrinologyAnorexia nervosa (differential diagnoses)Case-Control StudiesGhrelinbusinesshormones hormone substitutes and hormone antagonistsStroop effectDecision-making
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