Proceedings of the Annual Meeting of the Cognitive Science Society

What drives people’s exploration in complex scenarios wherethey have to actively acquire information? How do peopleadapt their selection of queries to the environment? We explorethese questions using Entropy Mastermind, a novel variantof the Mastermind code-breaking game, in which participantshave to guess a secret code by making useful queries. Partici-pants solved games more efficiently if the entropy of the gameenvironment was low; moreover, people adapted their initialqueries to the scenario they were in. We also investigatedwhether it would be possible to predict participants’ querieswithin the generalized Sharma-Mittal information-theoreticframework. Although predicting individual queries was dif-ficult, the modeling framework offered important insights onhuman behavior. Entropy Mastermind opens up rich possibili-ties for modeling and behavioral research.