Imaginary worlds are extremely successful. The most popular fictions produced in the last few decades contain such a fictional world. They can be found in all fictional media, from novels (e.g., Lord of The Rings and Harry Potter) to films (e.g., Star Wars and Avatar), video games (e.g., The Legend of Zelda and Final Fantasy), graphic novels (e.g., One Piece and Naruto), and TV series (e.g., Star Trek and Game of Thrones), and they date as far back as ancient literature (...) (e.g., the Cyclops Islands in The Odyssey, 850 BCE). Why such a success? Why so much attention devoted to non-existent worlds? In this paper, we propose that imaginary worlds co-opt our preferences for exploration, which have evolved in humans and nonhuman animals alike, to propel individuals toward new environments and new sources of reward. Humans would find imaginary worlds very attractive for the very same reasons, and under the same circumstances, as they are lured by unfamiliar environments in real life. After reviewing research on exploratory preferences in behavioral ecology, environmental esthetics, neuroscience, and evolutionary and developmental psychology, we focus on the sources of their variability across time and space, which we argue can account for the variability of the cultural preference for imaginary worlds. This hypothesis can, therefore, explain the way imaginary worlds evolved culturally, their shape and content, their recent striking success, and their distribution across time and populations. (shrink)

This paper presents the Rational Action, Noisy Choice for Habituation (RANCH) model. The model was evaluated with adult looking time collected from a paradigm analogous to the infant habituation paradigm. And the model captured key patterns of looking time documented in developmental research: habituation and dishabituation.

Bayesian approaches to human cognition have been extensively advocated in the last decades, but sharp objections have been raised too within cognitive science. In this paper, we outline a diagnosis of what has gone wrong with the prevalent strand of Bayesian cognitive science (here labelled pure Bayesian cognitive science), relying on selected illustrations from the psychology of reasoning and tools from the philosophy of science. Bayesians’ reliance on so-called method of rational analysis is a key point of our discussion. We (...) tentatively conclude on a constructive note, though: an appropriately modified variant of Bayesian cognitive science can still be coherently pursued, as some scholars have noted. (shrink)

Previous research suggests that curiosity is sometimes induced by novel information one has no relevant knowledge about, but it is sometimes induced by new information about something that one is familiar with and has prior knowledge about. However, the conditions under which novelty or familiarity triggers curiosity remain unclear. Using metacognitive confidence judgments as a proxy to quantify the amount of knowledge, this study evaluates the relationship between the amount of relevant knowledge and curiosity. We reviewed previous studies on the (...) relationship between subjective curiosity and confidence and reanalyzed existing large‐sample data. The findings indicate that the relationship between curiosity and confidence differs depending on the nature of the stimuli: epistemic versus perceptual. Regarding perceptual stimuli, curiosity is stronger when individuals have lower confidence levels. By contrast, for epistemic stimuli, curiosity is stronger when individuals have higher confidence levels. These results suggest that curiosity triggered by perceptual stimuli is based on perceived novelty, whereas that triggered by epistemic stimuli is based on familiarity with prior knowledge. (shrink)

Our actions and decisions are regularly influenced by the social environment around us. Can social cues be leveraged to induce curiosity and affect subsequent behavior? Across two experiments, we show that curiosity is contagious: The social environment can influence people's curiosity about the answers to scientific questions. Participants were presented with everyday questions about science from a popular on‐line forum, and these were shown with a high or low number of up‐votes as a social cue to popularity. Participants indicated their (...) curiosity about the answers, and they were given an opportunity to reveal a subset of those answers. Participants reported greater curiosity about the answers to questions when the questions were presented with a high (vs. low) number of up‐votes, and they were also more likely to choose to reveal the answers to questions with a high (vs. low) number of up‐votes. These effects were partially mediated by surprise and by the inferred usefulness of knowledge, with a more dramatic effect of low up‐votes in reducing curiosity than of high up‐votes in boosting curiosity. Taken together, these results highlight the important role social information plays in shaping our curiosity. (shrink)

In our target article, we proposed that curiosity and creativity are both manifestations of the same novelty-seeking process. We received 29 commentaries from diverse disciplines that add insights to our initial proposal. These commentaries ultimately expanded and supplemented our model. Here we draw attention to five central practical and theoretical issues that were raised by the commentators: (1) The complex construct of novelty and associated concepts; (2) the underlying subsystems and possible mechanisms; (3) the different pathways and subtypes of curiosity (...) and creativity; (4) creativity and curiosity “in the wild”; (5) the possible link(s) between creativity and curiosity. (shrink)

Using art and aesthetics as context, we explore the notion that curiosity and creativity emanate from a single novelty-seeking mechanism and outline support for the idea. However, we also highlight the importance of learning progress tracking in exploratory action and advocate for a nuanced understanding that aligns novelty-seeking with learnability. This, we argue, offers a more comprehensive framework of how curiosity and creativity are related.

Curiosity and creativity are expressions of the trade-off between leveraging that with which we are familiar or seeking out novelty. Through the computational lens of reinforcement learning, we describe how formulating the value of information seeking and generation via their complementary effects on planning horizons formally captures a range of solutions to striking this balance.

We received several commentaries both challenging and supporting our hypothesis. We thank the commentators for their thoughtful contributions, bringing together alternative hypotheses, complementary explanations, and appropriate corrections to our model. Here, we explain further our hypothesis, using more explicitly the framework of evolutionary social sciences. We first explain what we believe is the ultimate function of fiction in general (i.e., entertainment) and how this hypothesis differs from other evolutionary hypotheses put forward by several commentators. We then turn to the proximate (...) features that make imaginary worlds entertaining and, therefore, culturally successful. We finally explore how these insights may explain the distribution of imaginary worlds across time, space, age, and social classes. (shrink)

Novelty is neither necessary nor sufficient to link curiosity and creativity as stated in the target article. We point out the article's logical shortcomings, outline preconditions that may link curiosity and creativity, and suggest that curiosity and creativity may be expressions of a common epistemic drive.

The Novelty Seeking Model (NSM) places “novelty” at center stage in characterizing the mechanisms behind curiosity. We argue that the NSM's conception of novelty is too broad, obscuring distinct constructs. More critically, the NSM underemphasizes triggers of curiosity that better unify these constructs and that have received stronger empirical support: those that signal the potential for useful learning.

All forms of cognition, whether natural or artificial, are subject to constraints of their computing architecture. This assumption forms the tenet of virtually all general theories of cognition, including those deriving from bounded optimality and bounded rationality. In this letter, we highlight an unresolved puzzle related to this premise: what are these constraints, and why are cognitive architectures subject to cognitive constraints in the first place? First, we lay out some pieces along the puzzle edge, such as computational tradeoffs inherent (...) to neural architectures that give rise to rational bounds of cognition. We then outline critical next steps for characterizing cognitive bounds, proposing that some of these bounds can be subject to modification by cognition and, as such, are part of what is being optimized when cognitive agents decide how to allocate cognitive resources. We conclude that these emerging views may contribute to a more holistic perspective on the nature of cognitive bounds, as well as their alteration subject to cognition. (shrink)