scholarly journals Cognition-mediated evolution of low-quality floral nectars

Science ◽  
2017 ◽  
Vol 355 (6320) ◽  
pp. 75-78 ◽  
Author(s):  
Vladislav Nachev ◽  
Kai Petra Stich ◽  
Clemens Winter ◽  
Alan Bond ◽  
Alan Kamil ◽  
...  
Keyword(s):  
Tropical Rainforest ◽  
Decision Makers ◽  
Value Functions ◽  
Physical Magnitude ◽  
Evolution Experiment ◽  
Physical Stimuli ◽  
Competition For Food ◽  
Multiple Value ◽  
Nonlinear Selection

Plants pollinated by hummingbirds or bats produce dilute nectars even though these animals prefer more concentrated sugar solutions. This mismatch is an unsolved evolutionary paradox. Here we show that lower quality, or more dilute, nectars evolve when the strength of preferring larger quantities or higher qualities of nectar diminishes as magnitudes of the physical stimuli increase. In a virtual evolution experiment conducted in the tropical rainforest, bats visited computer-automated flowers with simulated genomes that evolved relatively dilute nectars. Simulations replicated this evolution only when value functions, which relate the physical stimuli to subjective sensations, were nonlinear. Selection also depended on the supply/demand ratio; bats selected for more dilute nectar when competition for food was higher. We predict such a pattern to generally occur when decision-makers consider multiple value dimensions simultaneously, and increases of psychological value are not fully proportional to increases in physical magnitude.

scholarly journals Sailing Speed Optimization Model for Slow Steaming Considering Loss Aversion Mechanism

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Yuzhe Zhao ◽  
Jingmiao Zhou ◽  
Yujun Fan ◽  
Haibo Kuang
Keyword(s):  
Loss Aversion ◽  
Optimization Model ◽  
Value Function ◽  
Fitness Function ◽  
Decision Makers ◽  
Value Functions ◽  
Delivery Delay ◽  
Slow Steaming ◽  
Proposed Model ◽  
Speed Optimization

This paper analyses loss aversion mechanism (LAM) of the shipping company’s decision-makers about the risk-based decision (RBD) for slow steaming and generalizes a novel optimization model for the sailing speed through the trade-off between fuel consumption, SOx emissions and delivery delay. The value functions against the benchmark speed were constructed based on physiological expected utility (PEU) to reveal the features of loss aversion, and the objective function was derived from these value functions with the aim to optimize the sailing speed. After that, a Genetic Algorithm (GA) solution with fitness function and special operators was built to solve the proposed model. Finally, the model was applied to pinpoint the PEU for the optimal sailing speed against the benchmark speed, and the sensitivity of the model was discussed with different benchmark speeds, value function weights and input parameters. The analysis shows that the proposed model can assist the slow steaming RBD based on the inner feelings of the shipping company’s decision-makers, offering a novel tool for sailing speed optimization.

scholarly journals A Hybrid Algorithm in Reinforcement Learning for Crowd Simulation

2020 ◽  
Vol 8 (6) ◽  
pp. 5251-5255
Keyword(s):  
Reinforcement Learning ◽  
Value Function ◽  
Crowd Simulation ◽  
Value Functions ◽  
Q Learning ◽  
Efficient Measurement ◽  
Multi Agent ◽  
Hybrid Agent ◽  
Multiple Value ◽  
Transportation Applications

Exploiting the efficiency and stability of Dynamic Crowd, the paper proposes a hybrid crowd simulation algorithm that runs using multi agents and it mainly focuses on identifying the crowd to simulate. An efficient measurement for both static and dynamic crowd simulation is applied in tracking and transportation applications. The proposed Hybrid Agent Reinforcement Learning (HARL) algorithm combines the Q-Learning off-policy value function and SARSA algorithm on-policy value function, which is used for dynamic crowd evacuation scenario. The HARL algorithm performs multiple value functions and combines the policy value function derived from the multi agent to improve the performance. In addition, the efficiency of the HARL algorithm is able to demonstrate in varied crowd sizes. Two kinds of applications are used in Reinforcement Learning such as tracking applications and transportation monitoring applications for pretending the crowd sizes.

EURRECA’s Approach for Estimating Micronutrient Requirements

2011 ◽  
Vol 81 (4) ◽  
pp. 256-263 ◽  
Author(s):  
Christophe Matthys ◽  
Pieter van ‘t Veer ◽  
Lisette de Groot ◽  
Lee Hooper ◽  
Adriënne E.J.M. Cavelaars ◽  
...  
Keyword(s):  
Reference Values ◽  
Policy Decision ◽  
Individual Variability ◽  
The Body ◽  
Decision Makers ◽  
Nutrient Requirements ◽  
Factorial Approach ◽  
Dietary Reference Values ◽  
Health Policy Decision ◽  
Quantitative Integration

In Europe, micronutrient dietary reference values have been established by (inter)national committees of experts and are used by public health policy decision-makers to monitor and assess the adequacy of diets within population groups. The approaches used to derive dietary reference values (including average requirements) vary considerably across countries, and so far no evidence-based reason has been identified for this variation. Nutrient requirements are traditionally based on the minimum amount of a nutrient needed by an individual to avoid deficiency, and is defined by the body’s physiological needs. Alternatively the requirement can be defined as the intake at which health is optimal, including the prevention of chronic diet-related diseases. Both approaches are confronted with many challenges (e. g., bioavailability, inter and intra-individual variability). EURRECA has derived a transparent approach for the quantitative integration of evidence on Intake-Status-Health associations and/or Factorial approach (including bioavailability) estimates. To facilitate the derivation of dietary reference values, EURopean micronutrient RECommendations Aligned (EURRECA) is developing a process flow chart to guide nutrient requirement-setting bodies through the process of setting dietary reference values, which aims to facilitate the scientific alignment of deriving these values.

Haunted by a Doppelgänger

2014 ◽  
Vol 61 (1) ◽  
pp. 12-22 ◽  
Author(s):  
Bettina von Helversen ◽  
Stefan M. Herzog ◽  
Jörg Rieskamp
Keyword(s):  
Relevant Information ◽  
Psychological Research ◽  
Decision Makers ◽  
Human Judgment ◽  
Rule Based ◽  
New Employees ◽  
High Performing ◽  
Facial Similarity ◽  
Similarity Effect ◽  
Judgment Strategy

Judging other people is a common and important task. Every day professionals make decisions that affect the lives of other people when they diagnose medical conditions, grant parole, or hire new employees. To prevent discrimination, professional standards require that decision makers render accurate and unbiased judgments solely based on relevant information. Facial similarity to previously encountered persons can be a potential source of bias. Psychological research suggests that people only rely on similarity-based judgment strategies if the provided information does not allow them to make accurate rule-based judgments. Our study shows, however, that facial similarity to previously encountered persons influences judgment even in situations in which relevant information is available for making accurate rule-based judgments and where similarity is irrelevant for the task and relying on similarity is detrimental. In two experiments in an employment context we show that applicants who looked similar to high-performing former employees were judged as more suitable than applicants who looked similar to low-performing former employees. This similarity effect was found despite the fact that the participants used the relevant résumé information about the applicants by following a rule-based judgment strategy. These findings suggest that similarity-based and rule-based processes simultaneously underlie human judgment.

Recognizing Users of the Recognition Heuristic

2008 ◽  
Vol 55 (6) ◽  
pp. 394-401 ◽  
Author(s):  
Benjamin E. Hilbig ◽  
Rüdiger F. Pohl
Keyword(s):  
Decision Makers ◽  
Recognition Heuristic ◽  
Inference Strategy

The recognition heuristic is hypothesized to be a frugal inference strategy assuming that inferences are based on the recognition cue alone. This assumption, however, has been questioned by existing research. At the same time most studies rely on the proportion of choices consistent with the heuristic as a measure of its use which may not be fully appropriate. In this study, we propose an index to identify true users of the heuristic contrasting them to decision makers who incorporate further knowledge beyond recognition. The properties and the applicability of the proposed index are investigated in the reanalyses of four published experiments and corroborated by a new study drawn up to rectify the shortcomings of the reanalyzed experiments. Applying the proposed index to explore the influence of knowledge we found that participants who were more knowledgeable made use of the information available to them and achieved the highest proportion of correct inferences.

Description of the sources of stress for palliative-care nurses: Implications for decision makers

2013 ◽  
Author(s):  
Lise Fillion ◽  
◽  
Louise Saint-Laurent ◽  
Martine Fortier
Keyword(s):  
Palliative Care ◽  
Decision Makers

Convergent Research Approaches to Political-Legal Socialization: Implications for Decision Makers

1969 ◽  
Author(s):  
Merton S. Krause ◽  
James Becker ◽  
Daniel Druckman ◽  
Bert H. Early ◽  
Mark I. Oberlander ◽  
...  
Keyword(s):  
Decision Makers ◽  
Legal Socialization
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