Informavores: Active information foraging and human cognition

Informavores: Active information foraging and human cognition Doug Markant (Moderator) and Todd Gureckis Dept. of Psychology, New York University Bj¨orn Meder and Jonathan D. Nelson Center for Adaptive Behavior and Cognition, Max Planck Institute for Human Development Peter Pirolli Palo Alto Research Center Chen Yu Dept. of Psychological and Brain Sciences, Indiana University in humans. The symposium should appeal to a broad set of attendees including educators, developmental psychologists, cognitive modelers, and computer scientists. The influence of priors on sequential search decisions - Keywords: active learning, self-directed learning, information search, sensemaking Just as the body survives by ingesting negative entropy, so the mind survives by ingesting information. In a very general sense, all higher organisms are informavores. - Miller (1983) Doug Markant and Todd Gureckis Normative models of information acquisition predict that people’s search decisions should be strongly influenced by their prior beliefs, which capture the set of alternative hy- potheses they are considering. In the present experiments we tested whether people adjusted their information search be- havior in response to sequential changes in the prior. Par- ticipants played a search game in which they had to identify the shape and location of multiple hidden targets in a display (similar to the board game Battleship). During the task they were told that the set of possible shapes had changed, and the key question was whether they would adjust their search deci- sions according to the predictions of a normative model. Ma- nipulations of the prior included changes in the frequency of certain classes of targets as well as the introduction of higher- order constraints (e.g., that all targets would have the same shape). The results showed that an individual’s prior could be recovered from their sequences of search decisions, but that there were notable differences in their ability to adjust to certain changes in the hypothesis space, an effect that is not predicted by the normative model. We discuss the implica- tions of these findings for how people generate and represent hypotheses during the course of information foraging. Is people’s information search behavior sensitive to differ- ¨ Meder and Jonathan Nelson ent reward structures? - Bj orn In situations where humans actively acquire information for classification, information search preferentially maxi- mizes accuracy (Nelson et al., 2010). However, the goal of obtaining information to improve classification accuracy can strongly conflict with the goal of obtaining information for improving utility when there are asymmetries in costs and benefits for classification decisions (e.g., in many medical diagnosis situations). Is people’s information search behav- ior sensitive to such asymmetries? We addressed this ex- perimentally via multiple-cue probabilistic category-learning and information-search experiments, where the payoffs cor- responded either to accuracy, with equal rewards associ- ated with the two categories, or to an asymmetric payoff function with different rewards associated with each cate- Unlike a passive sponge floating in a sea of information, humans are active information foragers – informavores – who gather and consume new knowledge. From controlling the movement of our eyes to determining which sources of news to consult, judging the quality of alternative sources of in- formation is a critical part of our behavior. The goal of this symposium is to bring together researchers who are working to understand the cognitive processes underlying active in- formation foraging and how they interact with more general aspects of cognition. The study of active information search is in the midst of a renaissance. Psychological research from diverse areas rang- ing from developmental psychology (Schulz & Bonawitz, 2007), to higher level cognition (Nelson, 2005) to visual per- ception (Najemnik & Geisler, 2005) have begun to under- stand information gathering strategies in terms of a common set of computational principles. Simultaneous developments in machine learning on “active vision” and “active learn- ing” (Settles, 2009) have resulted in new algorithms that op- timize their own learning by focusing on useful training data. Similarly, models from optimal foraging theory from biology are being brought to bear on cognitive search processes both within and outside the mind (Pirolli, 2007; Todd, Hills, & Robbins, 2012). This symposium aims to bring together leading experts in this area to discuss how active information foraging can be understood from a diverse set of perspectives within cognitive science. Key themes include how prior knowledge influences search (Markant & Gureckis), how information and reward interact to determine choice (Meder & Nelson), developmen- tal patterns in information seeking behavior (Nelson et al.), information foraging in complex sensemaking tasks (Pirolli), and the allocation of attention during statistical word learn- ing (Yu). While each represents a distinct area of research, all discussants in the symposium share a core approach of apply- ing computational models to understand information search