All Stories

  1. Learning to choose between advisors, algorithmic and human, over repeated interactions.
  2. Predicting human decisions with behavioural theories and machine learning
  3. Behavior engineering using quantitative reinforcement learning models
  4. Underweighting of rare events in strategic games
  5. Using machine learning to create an adaptable, scalable, and interpretable behavioral model.
  6. Beyond analytic bounds: Re-evaluating predictive power in risky decision models
  7. Towards Choice Engineering
  8. Predicting the direction of human deviation from optimal choice
  9. AS-BEAST: Using machine learning to create an adaptable, scalable, and interpretable behavioral model
  10. mRAPID Study: Effect of Micro-incentives and Daily Deadlines on Practice Behavior
  11. Motivational drivers for serial position effects: Evidence from high-stakes legal decisions.
  12. Better results through more enforcement with milder punishments
  13. To predict human choice, consider the context
  14. To predict human choice, consider the context
  15. Enforcement policies: Frequency of inspection is more important than the severity of punishment
  16. Prediction oriented behavioral research and its relationship to classical decision research
  17. Underweighting of rare events in social interactions and its implications to the design of voluntary health applications
  18. Underweighting of rare events in social interactions and its implications to the design of voluntary health applications
  19. Complacency, panic, and the value of gentle rule enforcement in addressing pandemics
  20. On The Value of Alert Systems and Gentle Rule Enforcement in Addressing Pandemics
  21. The influence of biased exposure to forgone outcomes
  22. Perceived patterns in decisions from experience and their influence on choice variability and policy diversification: A response to Ashby, Konstantinidis, & Yechiam, 2017
  23. On the impact of experience on probability weighting in decisions under risk.
  24. From anomalies to forecasts: Toward a descriptive model of decisions under risk, under ambiguity, and from experience.
  25. Learning in settings with partial feedback and the wavy recency effect of rare events
  26. Reliance on small samples, the wavy recency effect, and similarity-based learning.