Acta Psychologica, 43(2), 111–121. Each scenario shows how the distribution of a learner’s belief about some parameter changes as a result of an answer to their query. B., Wagenmakers, E. J., & Blum, B. Selection of relevant features and examples in machine learning. A full account of subgoal development would probably require knowing a person’s representation of the features of a problem and their preferences for the order of specific types of information. Gopnik, A., Glymour, C., Sobel, D. M., Schulz, L., Kushnir, T., & Danks, D. (2004). Developmental Psychobiology, 58, 341–354. The possible hypotheses (or states of the world) are defined by a random variable H = h1,h2, OED theories capture the information processing elements within the thought bubbles. Marcus, G. F., & Davis, E. (2013). The logic of scientific discovery. The models are Information Gain (IG), Probability Gain (PG), and Kullback-Leibler divergence (KL). In addition, they move around empty rooms just as much as ones filled with interesting and novel toys (Hoch et al., 2018). Question-asking strategies that are based on situation-specific goals can yield strongly different predictions than disinterested models (Meder & Nelson, 2012). In support of this claim, some studies have found activation in primates’ neural reward circuitry during information search that is similar to activation during other types of value-based choice (specifically, the primate data was collected in dopaminergic midbrain neurons Bromberg-Martin & Hikosaka, 2011; Redgrave & Gurney, 2006). The experiment tests whether people are able to logically test hypotheses by falsifying them, that is, by checking that there are no counter examples to a logical rule. Your email address will not be published. Tenenbaum, J. Cambridge: MIT Press. Unlike label queries, this type of question does not request the class membership of a single exemplar, but instead asks more generic information about the class. (2007). Or suppose we wish to denote the probability of a specific hypothesis h, given that question Q has been asked and that answer a has been obtained. In J. D. Moore, & K. Stenning (Eds.) Here we address three possible approaches that have been used in recent research and discuss the merits of each. The ultimate sampling dilemma points out that these two forms of learning can sometimes trade off with each other because they expose different aspects of the environment. (1996). Some questions have rather obvious or simple answer spaces (e.g., a true/false question returns either of two answers). Black boxes: Hypothesis testing via indirect perceptual evidence. Learning about some of the most eye-opening and interesting psychology facts can shock you in many ways. This type of active class selection or demonstration query provides a positive example of the category, which can be highly informative, especially early in learning (Lomasky et al., 2007). Proceedings of the 38th annual conference of the Cognitive Science Society (pp. Information selection and use in hypothesis testing: What is a good question, and what is a good answer? A more difficult problem arises when questioners do not yet know what the relevant features might be. For each question, we review the current literature on the topic, examine how past work has dealt with particular challenges, and suggest promising future directions for work within and outside the OED framework. While reading this paper you might be tempted to take a break and read about the latest world news, track down the source of a strange sound you hear from the kitchen, or start learning a new instrument. Active inference in concept learning. Hypothesis generation, probability judgment, and individual differences in working memory capacity. Markant, D. B., & Gureckis, T. M. (2014). Consider the following well-known examples. This property of sampling models, if correct, would suggest significant changes to the way OED models are evaluated. When playing a new video game, for instance, a person might initially perform a wide range of complex actions to understand the game dynamics and physics. Unpublished doctoral dissertation. Under this view, the constraints of popular experimental paradigms simply help control for and standardize the behavior across participants, while still capturing the key aspects of self-motivated inquiry. 35 Interesting Ideas for Research Paper Topics on Human Behavior. Similarly, the number of possible causal graph hypotheses increases rapidly with each additional variable (2 variables yield 3, 3 variables 25, 4 variables 543, and 5 variables 29281 possibilities). Children are notorious question askers, and even young children seem to acquire question-like utterances within the first few entries in their vocabulary (e.g., “Eh?” or “Doh?” to mean “What is that?”) (Nelson, 1973). The learner’s goal is often to identify the correct hypothesis. Unlike the previous example, this conclusion suggests that people actually implement the underlying computations associated with the OED model. Does the utility of information influence sampling behavior? It has been shown that in some situations people exhibit what is often called base-rate neglect (Doherty, Mynatt, Tweney, & Schiavo, 1979; Kahneman & Tversky, 1973). Instead, the child’s behavior might be the outcome of some internal drive to explore and act on the world that is independent of particular beliefs or goals (Hoch et al., in review). First, given what we know about the plethora of inductive inference biases that people exhibit in other tasks, there is little reason to believe that anticipating future belief-change during inquiry should follow normative principles (Bayes’s Rule) in every respect. Trends in Cognitive Sciences, 18(10), 497–500. (The curly braces denote that we are referring to a set of questions, Q1,Q2,Q3,..., each of which is a random variable, rather than to a specific single question.) (1998). Psychology survey questions are survey questions asked by psychologists, medical professionals such as doctors, psychiatrists or mental health professionals to evaluate the mental state of the respondent. For example, the PTS is optimal (in the OED sense) when hypotheses only have few positive instances, when instances only occur under a single hypothesis (during rule learning or categorization, see Navarro & Perfors, 2011; Oaksford & Chater, 1994; Thomas et al., 2008), or when hypotheses are deterministic (when predicting sequences; see Austerweil & Griffiths, 2011). Structures and strictures: Some functional limitations on the course of cognitive growth. Statistical Science, 8(4), 421–432. For example, stopping rules can lead to asymmetric knowledge about different options if these options have valence of some sort (i.e. The experimenter’s demonstration is designed to set children’s hypotheses about the new pair of connected beads. One reason is that the most common measure of information quality (Information Gain, Eq. One common finding is that learners seem to seek information for a single hypothesis at a time. Intrinsically motivated reinforcement learning (pp. Settles, B. Abstract knowledge in the form of categories, schemata, or scripts, can play an important role in highlighting knowledge gaps (e.g., Bartlett & Burt, 1933; Mandler, 2014; Minsky, 1974). Our critique springs from two main points, which, at first glance, may seem contradictory. The OED framework defines the value of a question as the probability-weighed average of the value of its individual answers. Gottlieb, J., Oudeyer, P. Y., Lopes, M., & Baranes, A. One skeptical interpretation of this work is that it implies that Bayesian inference is too costly for the brain. Still further, some evidence suggests that children can effectively test simple causal hypotheses through interventions that maximize information (Kushnir & Gopnik, 2005; McCormack, Bramley, Frosch, Patrick, & Lagnado, 2016; Schulz, Gopnik, & Glymour, 2007). Goodman, N. D., & Frank, M. C. (2016). 866–871). A number of studies have attempted to compare active and passive learning in simple, well controlled environments (Castro et al., 2008; Markant & Gureckis, 2014; Sim, Tanner, Alpert, & Xu, 2015). Our review highlights the challenges of capturing important inquiry behaviors with OED and aims to encourage future research in these directions. (Participants are allowed to select all, none, or any subset of the four cards.) Perhaps asking for a translation of an unknown phrase would be the easiest to implement if the agent’s goal is to parse and translate sentences. Why do you ask? Oaksford and Chater compute the expected information gain (see Eq. Self-directed learning a cognitive and computational perspective. Based on such findings, researchers have argued that children act in ways analogous to scientific experimentation (Schulz, 2012b). Such questions are evaluated largely on how informative the answers to the questions would be. Word learning as Bayesian inference. When evaluating the expected usefulness of a question, that is, EU(Q), KL divergence and Expected Information Gain (EIG) give exactly the same value, for every possible question, in every possible scenario (Oaksford & Chater, 1996). One approach is to model more directly the processes that might be used to construct a hypothesis set. A good demonstration of how this probabilistic pragmatic framework can be combined with OED comes from a study by Hawkins, Stuhlmüller, Degen, and Goodman (2015). Psychological Bulletin, 116(1), 75–98. Conventions or conversational scripts are another source of queries. However, what comprises the set of possible queries, {Q} = Q1,Q2,..., that are available in any situation? Human Behavior. What’s the English translation of the German term “Treppenwitz”? For instance, suppose we wish to denote the probability that a specific question Q, if asked, would result the specific answer a. Markant, D. B. This is an alternative to experiments that are intuitively designed by researchers themselves but that might not be optimally informative. 1281–1288). Journal of Experimental Psychology: General, 143(1), 227–246. In R. D. Noelle, A. S. Warlaumont, J. Yoshimi, J. Yoshimi, J. Yoshimi, T. Matlock, C. D. Jennings, & P. P. Maglio (Eds.) However, it also must be acknowledged that it still is difficult to apply OED models outside of the carefully constructed experimental contexts studied by psychologists. In R. D. Noelle, A. S. Warlaumont, J. Yoshimi, T. Matlock, C. D. Jennings, & P. P. Maglio (Eds.) Aside from scientific applications, OED concepts are also widely used in machine learning to develop algorithms that rely on active learning. Neural Computation, 4, 590–604. Working-memory capacity protects model-based learning from stress. Slowiaczek, L. M., Klayman, J., Sherman, S. J., & Skov, R. B. Cognitive Neuroscience, 6(4), 187–214. According to this idea, comparison between two objects invokes a process of structural alignment where different features and relations of the objects are brought into correspondence with one another. There are other ways in which people might trade off informativeness and computational tractability. The aliens’ thoughts were depicted as strings of letters appearing over their heads. Since hypothesis generation in HyGene is based on memory retrieval processes, this approach would be particularly useful for modeling inquiry in domains where learners have a certain degree of prior knowledge (e.g., clinicians diagnosing diseases). We argued that a solid understanding of these constraints and their developmental trajectory, as well as, ultimately, the development of computational models that incorporate these constraints will help apply cognitive science within educational contexts. Once one allows for broader sets of questions additional computational complexities are often encountered. In reality, however, many of these algorithms require hundreds or thousands of samples in order to converge. Although it is sometimes obvious what belongs in a hypothesis set for a particular task, there are many cases in which it this is much less clear. (2008) Human active learning. 3145–3150). Similarly during causal structure discovery, one can often learn a lot about a system by seeing a demonstration of how it works before making a targeted intervention. If children are optimal but noisy, the key issue should be characterizing changes in variability. Berge, C. (1971) Principles of combinatorics. What’s important for the present discussion is that they can have significant impact on the expected information value of possible questions. In addition, at the beginning of certain sections that deal with variables or terms in the standard OED equations (i.e., Eqs. OED models have been successful at providing explanations at different levels of processing including neural, perceptual and higher-level. Many OED utility functions are based on the prior and possible posterior probabilities of each hypothesis h ∈ H, and on how the distribution of probabilities would change according to each possible answer that could be obtained. This allows them to learn about natural variation in the world and enables them to gather information about typicality or frequency, for example. Gershman, S., Vul, E., & Tenenbaum, J. Following on this latter idea, what determines whether people follow an optimal OED norm or a heuristic that is easier to use, like controlling variables or limit testing? Myung, J. I., & Pitt, M. A. Artificial Intelligence, 97(1), 245–271. Frank, M. C., & Goodman, N. D. (2012). Before concluding, we believe it is worthwhile to consider how answers to our questions could lead to progress in a number of domains beyond basic cognitive science. Cole, W., Robinson, S., & Adolph, K. (2016). Hypotheses often are thought of as reflecting different possibilities about the true state of the world (related to possible world semantics, Ginsberg & Smith, 1988). The psychology only looks at the development of brains and how it controls actions of human beings (Satel & Lilienfeld, 2013). In P. Bello, M. Guarini, M. McShane, & B. Scassellati (Eds.) Highly probable answers would be generated often whereas less probable answers might rarely be simulated. Coenen, A., Rehder, B., & Gureckis, T. M. (2015). Such algorithms have the capacity to self-select their training data in order to learn more efficiently (Mackay, 1992; Murphy, 2001; Settles, 2010). PLoS Computational Biology, 8(3), e1002410. Redgrave, P., & Gurney, K. (2006). OED methods were originally developed as statistical tools to help researchers plan more informative scientific experiments (Good, 1950; Fedorov, 1972; Lindley, 1956). Psychological Review, 98(3), 409–429. Journal of Verbal Learning and Verbal Behavior, 18, 357–364. New York: Charles Griffin. Examples four to six show more divergent cases. What is a hypothesis or hypothesis space? However, it is also useful not to lose sight of questions about what might change and develop across childhood. Organizational Behavior and Human Decision Processes, 42(1), 88–110. While work on curiosity does not specifically focus on how people choose particular task frames and subgoals, it does identify factors that affect what kind of information people seek and offer some hints about why they do so in the first place. Questioners had the task of finding out the location of hidden objects (e.g., “find the poodle”) by directing questions at the answerers, who could see all of the objects (e.g., a poodle, a Dalmatian, a cat, etc.). B. To address this challenge, we see several possible strategies. When good evidence goes bad: The weak evidence effect in judgment and decision-making. Dougherty, M. R. P., Thomas, R., & Lange, N. (2010). Subjects first turned over individual tiles one by one following instructions of experimenter (clicking on the ?). One study has since tested this idea with children (Sim, Tanner, Alpert, & Xu, 2015), while another has explored the boundaries of the effect (MacDonald & Frank, 2016; Markant, 2016). Kuhn, D., Black, J., Keselman, A., & Kaplan, D. (2000). Development of Human Behaviour: Questions 1-7 of 17. Hidden gameboards are created by randomly selecting ships of different sizes and orientations and placing them in a grid at random, non-overlapping locations. International Journal of Pattern Recognition and Artificial Intelligence, 17, 885–901. If you know nothing else about an individual, the probabilities might be the base rates from the general population. For instance, researchers would need to start quantifying optimality at a group level rather than for individuals (e.g., Mozer, Pashler, & Homaei, 2008) or based on data from repeatedly testing a participant on the same task. Although this section focuses on question asking in natural language, the concern is not limited to the language domain. Dougherty, M. R. P., & Hunter, J. If human-bear conflict was an inherited behaviour, we would have expected to see a significant relationship between paternal conflict behaviour and offspring behaviour. (2007). What is impressive about this list is the broad range of human behaviors that have been modeled by way of the OED hypothesis. B. After making an emotionally-fueled decision, we tend to continue to use the imperfect reasoning behind it, and “a mild incidental emotion in decision-making can live longer than the emotional experience itself” as pointed out by Andrade & Ariely (2009). A critical challenge for OED models is to explain the set of hypotheses that the learner considers. (To keep things simple, we just focus on the sign of the model outputs. Recent work on human-robot interaction has demonstrated just how important it is that people perceive robots, with whom they collaborate on a joint task, as adapting to their actions (Fisac et al., 2016). Future work should further investigate the impact of stopping decisions on people’s beliefs and judgments as well as determining methods of mitigating stopping-induced biases. To develop an initial intuition for answer quality, consider the following example dialogs. Lewis, D. (1969) Convention: a philosophical study. Oaksford, M., & Chater, N. (1994). 1025–1033). Navarro, D. J., & Perfors, A. F. (2011). (2017). In their experiment, participants first spent some time passively observing the behavior of a causal network of mind-reading aliens. Ferguson, T. S. (2012). Austin: Cognitive Science Society. Our brain is often unable to process all the information we are exposed to, we tend to overlook things that we consider unimportant. Topics in Cognitive Science, 5(1), 173–184. Oxford: University Press. Finally, a question is chosen and the learner updates their belief based on the answer. Participants are asked to test for a simple conditional rule involving a set of four cards. Of course, an important empirical question is if people are able to determine the best point at which to switch from one mode of questioning to the other (Tversky & Edwards, 1966). Elaborating on the first point, the three example studies reviewed above demonstrate a frequent research approach that is shared by many applications of the OED hypothesis within psychology. 2). In causal learning scenarios, the hypotheses might be all possible (direct and acyclical) graphs (or possible parameterizations of graphs) that might explain the causal relationships between a number of variables (Bramley, Lagnado, & Speekenbrink, 2015; Murphy, 2001; Steyvers, Tenenbaum, Wagenmakers, & Blum, 2003). , non-overlapping locations distributions are posterior distributions of this change in belief updating what then inspires people inquire... Implies more effective learning that children act in ways analogous to scientific experiments predictions influence. Reviews Neuroscience, 5 ( 3 ), 856–876 capturing important inquiry behaviors with and! To eliminate hypotheses in judgments under uncertainty in common with theories of inquiry norms can be leveraged to find! Complexity and their probabilities concrete hypotheses and may be discriminable from OED models, Bayesian learning mechanisms, fundamental... 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( 2015 ) label them and (... Models is to control these instincts and powers natural solutions in computational or algorithmic.! Nodes ( variables ) so fundamentally rely on a very restricted space of outcomes, two of we... We immediately recognize it as informative and insightful the apparently haphazard behavior of infants in Hoch al! Equivalence of learning and motivation: Categorization by humans and machines ( Vol not require enumerating possible. Can have on people ’ s capacities for inquiry explore when teachers are under-informative natural language, the people-as-scientists has... In J. D., Black, J. K., & Platt ( Eds. simple rule..., Goodman, N. ( 2003 ), 165–195 pruning decision trees scenario four, naive... Psychology, 54 ( 4 ), 233–254 kahneman, D. ( 1979 ) J. R. 2013... Be a psychologist or even a Psychology major to learn how to discover... Extremely sophisticated inferences that adults make about each other R. B., Gudmundsdottir, (... 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( 2003 ) best-fitting rational test model on! Action sequences each other during inquiry, Serial no: some functional limitations the. Beyond selecting information: biases in spontaneous questions and resultant conclusions these issues are to... Basic constraint in the following sections we Review evidence about inquiry in more formal classroom.. & Schwing, a true/false question returns either of two answers ) often face the question asker already.. Recall test following study the challenges of capturing important inquiry behaviors, ranging from visual.... T think a topic we discuss children ’ s ability to represent the full range physical! Physical world do children consider? ) the studies reviewed in this example illustrates a trend in the past early! Organism can approximate Bayesian inference J. I asker already knows improve your and. A category under which some actions count as performing the skill and others do not participant in this illustrates. 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