1. The theoretical beauty and fertility of sampling approaches: a historical and meta-theoretical review Klaus Fiedler, Peter Juslin and Jerker Denrell; 2. Homo ordinalus and sampling models: the past, present, and future decision by sampling Gordon D. A. Brown and Lukasz Walasek; 3. In decisions from experience what you see is up to your sampling of the world Timothy J. Pleskac and Ralph Hertwig; 4. The hot stove effect Jerker Denrell and Gaël Le Mens; 5. The J/DM separation paradox and the reliance on small samples hypothesis Ido Erev and Ori Plonsky; 6. Sampling as preparedness in evaluative learning Mandy Hütter and Zachary Adolph Niese; 7. The dog that didn't bark: Bayesian approaches to reasoning Brett K. Hayes, Saoirse Connor Desai, Keith Ransom and Charles Kemp; 8. Unpacking intuitive and analytica memory sampling in multiple-cue judgment August Collsiöö, Joakim Sundh and Peter Juslin; 9. Biased preferences through exploitation Chris Harris and Ruud Custers; 10. Evaluative consequences of sampling distinct information Hans Alves, Alex Koch, and Christian Unkelbach; 11. Information sampling in contingency learning: sampling strategies and their consequences for (pseudo-)contingency Franziska M. Bott and Thorsten Meiser; 12. The collective hot stove effect Gaël Le Mens, Balázs Kovác, Judith Avrahami, and Yaakov Kareev; 13. Sequential decisions from sampling: inductive generation of stopping decisions using instance-based learning theory Cleotilde Gonzales and Palvi Aggarwal; 14. Thurstonian uncertainty in self-determined judgment and decision making Johannes Prager, Klaus Fiedler, and Linda McCaughey; 15. The information cost-benefit trade-off as a sampling problem in information search Linda McCaughey, Johannes Prager, and Klaus Fiedler; 16. Heuristic social sampling Thorsten Pachur and Christin Schulze; 17. Social sampling for judgments and predictions of societal trends Henrik Olsson, Mirta Galesic and Wändi Bruine de Bruin; 18. Group-motivated sampling: from skewed experiences to biased evaluations Yrian Derreumaux, Robin Bergh, Marcus Lindskog and Brent Hughes; 19. Opinion homogenization and polarization: three sampling models Elizaveta Konovalova and Gaël Le Mens; 20. An introduction to psychologically plausible sampling schemes for approximating Bayesian inference Jian-Qiao Zhu, Nick Chater, Pablo León-Villagrá, Jake Spicer, Joakim Sundh and Adam Sanborn; 21. Approximating Bayesian inference through internal sampling Joakim Sundh, Adam Sanborn, Jian-Qiao Zhu, Jake Spicer, Pablo León-Villagrá and Nick Chater; 22. Sampling data, beliefs, and actions Erik Brockbank, Cameron Holdaway, Daniel Acosta-Kane, and Edward Vul.