Putting bandits into context: How function learning supports decision making

The authors introduce the contextual multi-armed bandit task as a framework to investigate learning and decision making in uncertain environments. In this novel paradigm, participants repeatedly choose between multiple options in order to maximize their rewards. The options are described by a number of contextual features which are predictive of the rewards through initially unknown functions. From their experience with choosing options and observing the consequences of their decisions, participants can learn about the functional relation between contexts and rewards and improve their decision strategy over time. In three experiments, the authors explore participants’ behavior in such learning environments. They predict participants’ behavior by context-blind (mean-tracking, Kalman filter) and contextual (Gaussian process and linear regression) learning approaches combined with different choice strategies. Participants are mostly able to learn about the context-reward functions and their behavior is best described by a Gaussian process learning strategy which generalizes previous experience to similar instances. In a relatively simple task with binary features, they seem to combine this learning with a probability of improvement decision strategy which focuses on alternatives that are expected to lead to an improvement upon a current favorite option. In a task with continuous features that are linearly related to the rewards, participants seem to more explicitly balance exploration and exploitation. Finally, in a difficult learning environment where the relation between features and rewards is nonlinear, some participants are again well-described by a Gaussian process learning strategy, whereas others revert to context-blind strategies

Unraveling the Interconnection Patterns Across Lung Microbiome, Respiratory Diseases, and COVID-19.

Albeit the lungs were thought to be sterile, recent scientific data reported a microbial microbiota in the lungs of healthy individuals. Apparently, new developments in technological approachesincluding genome sequencing methodologies contributed in the identification of the microbiota and shed light on the role of the gut and lung microbiomes in the development of respiratory diseases. Moreover, knowledge of the human microbiome in health may act as a tool for evaluating characteristic shifts in the case of disease. This review paper discusses the development of respiratory disease linked to the intestinal dysbiosis which influences the lung immunity and microbiome. The gastrointestinal-lung dialogue provides interesting aspects in the pathogenesis of the respiratory diseases. Lastly, we were further interested on the role of this interconnection in the progression and physiopathology of newly emergedCOVID-19

Magnitude and incentives: Revisiting the overweighting of extreme events in risky decisions from experience

Recent experimental evidence in experience-based decision-making suggests that people are more risk seeking in the gains domain relative to the losses domain. This critical result is at odds with the standard reflection effect observed in description-based choice and explained by Prospect Theory. The so-called reversed-reflection effect has been predicated on the extreme-outcome rule, which suggests that memory biases affect risky choice from experience. To test the general plausibility of the rule, we conducted two experiments examining how the magnitude of prospective outcomes impacts risk preferences. We found that while the reversed-reflection effect was present with small-magnitude payoffs, using payoffs of larger magnitude brought participants’ behavior back in line with the standard reflection effect. Our results suggest that risk preferences in experience-based decision-making are not only affected by the relative extremeness but also by the absolute extremeness of past events

The Role of Unconscious Influences on Decision-Making under Uncertainty: Behavioural and Computational Approaches

How do people make decisions in uncertain environments and what types of knowl- edge control their choices? Can our decisions be guided by unconscious influences or intuitive “gut” feelings? According to the Somatic Marker Hypothesis, a popular account of the role of affect in decision-making, emotion-based signals can guide our decisions in uncertain environments outside awareness. However, evidence for this claim can be ques- tioned on the grounds of inadequate and insensitive assessments of conscious knowledge. In this work, variations of a classic experience-based decision-making paradigm, the Iowa Gambling Task (IGT), are employed in combination with subjective measures of awareness in order to investigate the role played by unconscious influences. Specifically, the validity of post-decision wagering as a sensitive and bias-free measure of conscious content is examined and contrasted to confidence ratings and quantitative reports. The results demonstrate the inadequacy of post-decision wagering as a direct measure of conscious knowledge and also question the claim that implicit processes influence decision- making. In order to measure and understand the cognitive and psychological processes un- derlying performance on the IGT, computational modeling analyses are undertaken to provide deeper insights into the dynamics of decision-making. Reinforcement-learning models are evaluated using different model comparison techniques and a computational model of confidence ratings in decision-making under uncertainty is developed

Spin Polaron Effective Magnetic Model for La_{0.5}Ca_{0.5}MnO_3

The conventional paradigm of charge order for La_{1-x}Ca_xMnO_3 for x=0.5 has been challenged recently by a Zener polaron picture emerging from experiments and theoretical calculations. The effective low energy Hamiltonian for the magnetic degrees of freedom has been found to be a cubic Heisenberg model, with ferromagnetic nearest neighbor and frustrating antiferromagnetic next nearest neighbor interactions in the planes, and antiferromagnetic interaction between planes. With linear spin wave theory and diagonalization of small clusters up to 27 sites we find that the behavior of the model interpolates between the A and CE-type magnetic structures when a frustrating intraplanar interaction is tuned. The values of the interactions calculated by ab initio methods indicate a possible non-bipartite picture of polaron ordering differing from the conventional one.Comment: 21 pages and 8 figures (included), Late

Prognostic models for outcome prediction in patients with chronic obstructive pulmonary disease: systematic review and critical appraisal

OBJECTIVE: To map and assess prognostic models for outcome prediction in patients with chronic obstructive pulmonary disease (COPD). DESIGN: Systematic review. DATA SOURCES: PubMed until November 2018 and hand searched references from eligible articles. ELIGIBILITY CRITERIA FOR STUDY SELECTION: Studies developing, validating, or updating a prediction model in COPD patients and focusing on any potential clinical outcome. RESULTS: The systematic search yielded 228 eligible articles, describing the development of 408 prognostic models, the external validation of 38 models, and the validation of 20 prognostic models derived for diseases other than COPD. The 408 prognostic models were developed in three clinical settings: outpatients (n=239; 59%), patients admitted to hospital (n=155; 38%), and patients attending the emergency department (n=14; 3%). Among the 408 prognostic models, the most prevalent endpoints were mortality (n=209; 51%), risk for acute exacerbation of COPD (n=42; 10%), and risk for readmission after the index hospital admission (n=36; 9%). Overall, the most commonly used predictors were age (n=166; 41%), forced expiratory volume in one second (n=85; 21%), sex (n=74; 18%), body mass index (n=66; 16%), and smoking (n=65; 16%). Of the 408 prognostic models, 100 (25%) were internally validated and 91 (23%) examined the calibration of the developed model. For 286 (70%) models a model presentation was not available, and only 56 (14%) models were presented through the full equation. Model discrimination using the C statistic was available for 311 (76%) models. 38 models were externally validated, but in only 12 of these was the validation performed by a fully independent team. Only seven prognostic models with an overall low risk of bias according to PROBAST were identified. These models were ADO, B-AE-D, B-AE-D-C, extended ADO, updated ADO, updated BODE, and a model developed by Bertens et al. A meta-analysis of C statistics was performed for 12 prognostic models, and the summary estimates ranged from 0.611 to 0.769. CONCLUSIONS: This study constitutes a detailed mapping and assessment of the prognostic models for outcome prediction in COPD patients. The findings indicate several methodological pitfalls in their development and a low rate of external validation. Future research should focus on the improvement of existing models through update and external validation, as well as the assessment of the safety, clinical effectiveness, and cost effectiveness of the application of these prognostic models in clinical practice through impact studies. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42017069247

Don't bet on it! Wagering as a measure of awareness in decision making under uncertainty

Can our decisions be guided by unconscious or implicit influences? According to the somatic marker hypothesis, emotion-based signals can guide our decisions in uncertain environments outside awareness. Postdecision wagering, in which participants make wagers on the outcomes of their decisions, has been recently proposed as an objective and sensitive measure of conscious content. In 5 experiments we employed variations of a classic decision-making assessment, the Iowa Gambling Task, in combination with wagering in order to investigate the role played by unconscious influences. We examined the validity of postdecision wagering by comparing it with alternative measures of conscious knowledge, specifically confidence ratings and quantitative questions. Consistent with a putative role for unconscious influences, in Experiments 2 and 3 we observed a lag between choice accuracy and the onset of advantageous wagering. However, the lag was eliminated by a change in the wagering payoff matrix (Experiment 2) and by a switch from a binary wager response to either a binary or a 4-point confidence response (Experiment 3), and wagering underestimated awareness compared to explicit quantitative questions (Experiments 1 and 4). Our results demonstrate the insensitivity of postdecision wagering as a direct measure of conscious knowledge and challenge the claim that implicit processes influence decision making under uncertainty

Uncertainty and exploration in a restless bandit task

Decision-making in noisy and changing environments requires a fine balance between exploiting knowledge about good courses of action and exploring the environment in order to improve upon this knowledge. We present an experiment in which participants made repeated choices between options for which the average rewards changed over time. Comparing a number of computational models of participants' behaviour in this task, we find evidence that a substantial number of them balanced exploration and exploitation by considering the probability that an option offers the maximum reward out of all the available options

Hydrodynamic forces on circular cylinders oscillating with small amplitude in still fluid or transverse to a free stream

In the present study we compare the hydrodynamic forces acting on circular cylinders oscillating in still fluid with corresponding oscillations transverse to a free stream. We find that at small amplitudes of motion the time history of the total force acting in the direction of oscillation in the presence of a free stream is virtually the same as in still fluid and in very good agreement with Stokes–Wang analytical solutions. However, the flow patterns around the cylinders that generate the consistent force history are remarkably disparate