UC Davis

How do people choose what book to read? At times, people choose to exploit well-known options that are likely to lead to high enjoyment. However, readers must also effectively explore novel books in order to reduce uncertainty in a way that allows for efficient learning about less-known alternatives that might also lead to high enjoyment. It is unknown precisely how and why readers make these sequential book selection decisions. By placing book options in a semantic embedding space, we show that people decide which book to explore using a structured generalization mechanism based on semantic similarities between known and unknown books and a directed exploration mechanism that incentivizes seeking books in high uncertainty. In addition, we demonstrate that people’s directed and random book exploration patterns are modulated by individual differences in curiosity, which fosters reading enjoyment and promotes exploring unfamiliar books. In summary, our study demonstrates that these exploration mechanisms guide readers' decisions about what books to read in a way that leads to high levels of enjoyment.