Simple Heuristics in a Social Game

Simple Heuristics in a Social World invites readers to discover the simple heuristics that people use to navigate the complexities and surprises of environments populated with others. The social world is a terrain where humans and other animals compete with conspecifics for myriad resources, including food, mates, and status, and where rivals grant the decision maker little time for deep thought, protracted information search, or complex calculations. Yet, the social world also encompasses domains where social animals such as humans can learn from one another and can forge alliances with one another to boost their chances of success. According to the book's thesis, the undeniable complexity of the social world does not dictate cognitive complexity as many scholars of rationality argue. Rather, it entails circumstances that render optimization impossible or computationally arduous: intractability, the existence of incommensurable considerations, and competing goals. With optimization beyond reach, less can be more. That is, heuristics--simple strategies for making decisions when time is pressing and careful deliberation an unaffordable luxury--become indispensible mental tools. As accurate as or even more accurate than complex methods when used in the appropriate social environments, these heuristics are good descriptive models of how people make many decisions and inferences, but their impressive performance also poses a normative challenge for optimization models. In short, the Homo socialis may prove to be a Homo heuristicus whose intelligence reflects ecological rather than logical rationality.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

Decision making in a human population living sustainably

The Tiwi people of northern Australia have managed natural resources continuously for 6000-8000 years. Tiwi management objectives and outcomes may reflect how they gather information about the environment. We qualitatively analyzed Tiwi documents and management techniques to examine the relation between the social and physical environment of decision makers and their decision-making strategies. We hypothesized that principles of bounded rationality, namely, the use of efficient rules to navigate complex decision problems, explain how Tiwi managers use simple decision strategies (i.e., heuristics) to make robust decisions. Tiwi natural resource managers reduced complexity in decision making through a process that gathers incomplete and uncertain information to quickly guide decisions toward effective outcomes. They used management feedback to validate decisions through an information loop that resulted in long-term sustainability of environmental use. We examined the Tiwi decision-making processes relative to management of barramundi (Lates calcarifer) fisheries and contrasted their management with the state government's management of barramundi. Decisions that enhanced the status of individual people and their attainment of aspiration levels resulted in reliable resource availability for Tiwi consumers. Different decision processes adopted by the state for management of barramundi may not secure similarly sustainable outcomes.

Efficacy of brief motivational intervention at army conscription to address alcohol use and related problems: a randomized controlled trial

Objectives: The aim of this study was to evaluate the efficacy of brief motivational intervention (BMI) in reducing alcohol use and related problems among binge drinkers randomly selected from a census of 20 year-old French speaking Swiss men and to test the hypothesis that BMI contributes to maintain low-risk drinking among non-bingers. Methods: Randomized controlled trial comparing the impact of BMI on weekly alcohol use, frequency of binge drinking and occurrence of alcohol-related problems. Setting: Army recruitment center. Participants: A random sample of 622 men were asked to participate, 178 either refused, or missed appointment, or had to follow military assessment procedures instead, resulting in 418 men randomized into BMI or control conditions, 88.7% completing the 6-month follow-up assessment. Intervention: A single face-to-face BMI session exploring alcohol use and related problems in order to stimulate behaviour change perspective in a non-judgmental, empathic manner based on the principles of motivational interviewing (MI). Main outcome measures: Weekly alcohol use, binge drinking frequency and the occurrence of 12 alcohol-related consequences. Results: Among binge drinkers, we observed a 20% change in drinking induced by BMI, with a reduction in weekly drinking of 1.5 drink in the BMI group, compared to an increase of 0.8 drink per week in the control group (incidence rate ratio 0.8, 95% confidence interval 0,66 to 0,98, p = 0.03). BMI did not influence the frequency of binge drinking and the occurrence of 12 possible alcohol-related consequences. However, BMI induced a reduction in the alcohol use of participants who, after drinking over the past 12 months, experienced alcohol-related consequences, i.e., hangover (-20%), missed a class (-53%), got behind at school (-54%), argued with friends (-38%), engaged in unplanned sex (-45%) or did not use protection when having sex (-64%). BMI did not reduce weekly drinking in those who experienced the six other problems screened. Among non-bingers, BMI did not contribute to maintain low-risk drinking. Conclusions: At army conscription, BMI reduced alcohol use in binge drinkers, particularly in those who recently experienced alcohol-related adverse consequences. No preventive effect of BMI was observed among non-bingers. BMI is an interesting preventive option in young binge drinkers, particularly in countries with mandatory army recruitment.

Development and validation of a clinical decision rule for the diagnosis of influenza.

INTRODUCTION: A clinical decision rule to improve the accuracy of a diagnosis of influenza could help clinicians avoid unnecessary use of diagnostic tests and treatments. Our objective was to develop and validate a simple clinical decision rule for diagnosis of influenza. METHODS: We combined data from 2 studies of influenza diagnosis in adult outpatients with suspected influenza: one set in California and one in Switzerland. Patients in both studies underwent a structured history and physical examination and had a reference standard test for influenza (polymerase chain reaction or culture). We randomly divided the dataset into derivation and validation groups and then evaluated simple heuristics and decision rules from previous studies and 3 rules based on our own multivariate analysis. Cutpoints for stratification of risk groups in each model were determined using the derivation group before evaluating them in the validation group. For each decision rule, the positive predictive value and likelihood ratio for influenza in low-, moderate-, and high-risk groups, and the percentage of patients allocated to each risk group, were reported. RESULTS: The simple heuristics (fever and cough; fever, cough, and acute onset) were helpful when positive but not when negative. The most useful and accurate clinical rule assigned 2 points for fever plus cough, 2 points for myalgias, and 1 point each for duration <48 hours and chills or sweats. The risk of influenza was 8% for 0 to 2 points, 30% for 3 points, and 59% for 4 to 6 points; the rule performed similarly in derivation and validation groups. Approximately two-thirds of patients fell into the low- or high-risk group and would not require further diagnostic testing. CONCLUSION: A simple, valid clinical rule can be used to guide point-of-care testing and empiric therapy for patients with suspected influenza.