Plans, Habits, and Theory of Mind

Doing things efficiently: Testing an account of why simple explanations are satisfying

People often find simple explanations more satisfying than complex ones. Across seven preregistered experiments, we provide evidence that this simplicity preference is not specific to explanations and may instead arises from a broader tendency to prefer completing goals in efficient ways. In each experiment, participants (total N=2820) learned of simple and complex methods for producing an outcome, and judged which was more appealing-either as an explanation why the outcome happened, or as a process for producing it. Participants showed similar preferences across judgments. They preferred simple methods as explanations and processes in tasks with no statistical information about the reliability or pervasiveness of causal elements. But when this statistical information was provided, preferences for simple causes often diminished and reversed in both kinds of judgments. Together, these findings suggest that people may assess explanations much in the same ways they assess methods for completing goals, and that both kinds of judgments depend on the same cognitive mechanisms.

A Hierarchical Bayesian Model of Adaptive Teaching

How do teachers learn about what learners already know? How do learners aid teachers by providing them with information about their background knowledge and what they find confusing? We formalize this collaborative reasoning process using a hierarchical Bayesian model of pedagogy. We then evaluate this model in two online behavioral experiments (N = 312 adults). In Experiment 1, we show that teachers select examples that account for learners' background knowledge, and adjust their examples based on learners' feedback. In Experiment 2, we show that learners strategically provide more feedback when teachers' examples deviate from their background knowledge. These findings provide a foundation for extending computational accounts of pedagogy to richer interactive settings.

Teaching Without Thinking: Negative Evaluations of Rote Pedagogy

When people make decisions, they act in a way that is either automatic ("rote"), or more thoughtful ("reflective"). But do people notice when others are behaving in a rote way, and do they care? We examine the detection of rote behavior and its consequences in U.S. adults, focusing specifically on pedagogy and learning. We establish repetitiveness as a cue for rote behavior (Experiment 1), and find that rote people are seen as worse teachers (Experiment 2). We also find that the more a person's feedback seems similar across groups (indicating greater rote-ness), the more negatively their teaching is evaluated (Experiment 3). A word-embedding analysis of an open-response task shows people naturally cluster rote and reflective teachers into different semantic categories (Experiment 4). We also show that repetitiveness can be decoupled from perceptions of rote-ness given contextual explanation (Experiment 5). Finally, we establish two additional cues to rote behavior that can be tied to quality of teaching (Experiment 6). These results empirically show that people detect and care about scripted behaviors in pedagogy, and suggest an important extension to formal frameworks of social reasoning.

Repeated rock, paper, scissors play reveals limits in adaptive sequential behavior

How do people adapt to others in adversarial settings? Prior work has shown that people often violate rational models of adversarial decision-making in repeated interactions. In particular, in mixed strategy equilibrium (MSE) games, where optimal action selection entails choosing moves randomly, people often do not play randomly, but instead try to outwit their opponents. However, little is known about the adaptive reasoning that underlies these deviations from random behavior. Here, we examine strategic decision-making across repeated rounds of rock, paper, scissors, a well-known MSE game. In experiment 1, participants were paired with bot opponents that exhibited distinct stable move patterns, allowing us to identify the bounds of the complexity of opponent behavior that people can detect and adapt to. In experiment 2, bot opponents instead exploited stable patterns in the human participants' moves, providing a symmetrical bound on the complexity of patterns people can revise in their own behavior. Across both experiments, people exhibited a robust and flexible attention to transition patterns from one move to the next, exploiting these patterns in opponents and modifying them strategically in their own moves. However, their adaptive reasoning showed strong limitations with respect to more sophisticated patterns. Together, results provide a precise and consistent account of the surprisingly limited scope of people's adaptive decision-making in this setting.

The temporal structure of goal-directed and habitual operant behavior

Operant behavior can reflect the influence of goal-directed and habitual processes. These can be distinguished by changes to response rate following devaluation of the reinforcing outcome. Whether a response is goal directed or habitual depends on whether devaluation affects response rate. Response rate can be decomposed into frequencies of bouts and pauses by analyzing the distribution of interresponse times. This study sought to characterize goal-directed and habitual behaviors in terms of bout-initiation rate, within-bout response rate, bout length, and bout duration. Data were taken from three published studies that compared sensitivity to devaluation following brief and extended training with variable-interval schedules. Analyses focused on goal-directed and habitual responding, a comparison of a habitual response to a similarly trained response that had been converted back to goal-directed status after a surprising event, and a demonstration of contextual control of habit and goal direction in the same subjects. Across experiments and despite responses being clearly distinguished as goal directed and habitual by total response rate, analyses of bout-initiation rate, within-bout rate, bout length, and bout duration did not reveal a pattern that distinguished goal-directed from habitual responding.

People infer communicative action through an expectation for efficient communication

Humans often communicate using body movements like winks, waves, and nods. However, it is unclear how we identify when someone’s physical actions are communicative. Given people’s propensity to interpret each other’s behavior as aimed to produce changes in the world, we hypothesize that people expect communicative actions to efficiently reveal that they lack an external goal. Using computational models of goal inference, we predict that movements that are unlikely to be produced when acting towards the world and, in particular, repetitive ought to be seen as communicative. We find support for our account across a variety of paradigms, including graded acceptability tasks, forced-choice tasks, indirect prompts, and open-ended explanation tasks, in both market-integrated and non-market-integrated communities. Our work shows that the recognition of communicative action is grounded in an inferential process that stems from fundamental computations shared across different forms of action interpretation.

Humans can quickly infer when someone’s body movements are meant to be communicative. Here, the authors show that this capacity is underpinned by an expectation that communicative actions will efficiently reveal that they lack an external goal.

Illusory Feelings, Elusive Habits: People Overlook Habits in Explanations of Behavior

Habits underlie much of human behavior. However, people may prefer agentic accounts that overlook habits in favor of inner states, such as mood. We tested this misattribution hypothesis in an online experiment of helping behavior (N = 809 adults) as well as in an ecological momentary assessment (EMA) study of U.S. college students' everyday coffee drinking (N = 112). Both studies revealed a substantial gap between perceived and actual drivers of behavior: Habit strength outperformed or matched inner states in predicting behavior, but participants' explanations of their behavior emphasized inner states. Participants continued to misattribute habits to inner states when incentivized for accuracy and when explaining other people's behavior. We discuss how this misperception could adversely influence self-regulation.

Moral dynamics: Grounding moral judgment in intuitive physics and intuitive psychology

When holding others morally responsible, we care about what they did, and what they thought. Traditionally, research in moral psychology has relied on vignette studies, in which a protagonist's actions and thoughts are explicitly communicated. While this research has revealed what variables are important for moral judgment, such as actions and intentions, it is limited in providing a more detailed understanding of exactly how these variables affect moral judgment. Using dynamic visual stimuli that allow for a more fine-grained experimental control, recent studies have proposed a direct mapping from visual features to moral judgments. We embrace the use of visual stimuli in moral psychology, but question the plausibility of a feature-based theory of moral judgment. We propose that the connection from visual features to moral judgments is mediated by an inference about what the observed action reveals about the agent's mental states, and what causal role the agent's action played in bringing about the outcome. We present a computational model that formalizes moral judgments of agents in visual scenes as computations over an intuitive theory of physics combined with an intuitive theory of mind. We test the model's quantitative predictions in three experiments across a wide variety of dynamic interactions.

Model based planners reflect on their model-free propensities

Dual-reinforcement learning theory proposes behaviour is under the tutelage of a retrospective, value-caching, model-free (MF) system and a prospective-planning, model-based (MB), system. This architecture raises a question as to the degree to which, when devising a plan, a MB controller takes account of influences from its MF counterpart. We present evidence that such a sophisticated self-reflective MB planner incorporates an anticipation of the influences its own MF-proclivities exerts on the execution of its planned future actions. Using a novel bandit task, wherein subjects were periodically allowed to design their environment, we show that reward-assignments were constructed in a manner consistent with a MB system taking account of its MF propensities. Thus, in the task participants assigned higher rewards to bandits that were momentarily associated with stronger MF tendencies. Our findings have implications for a range of decision making domains that includes drug abuse, pre-commitment, and the tension between short and long-term decision horizons in economics.

Accurate emotion prediction in dyads and groups and its potential social benefits

Emotion dynamics vary considerably from individual to individual and from group to group. Successful social interactions require people to track this moving target in order to anticipate the thoughts, feelings, and actions of others. In two studies, we test whether people track others' emotional idiosyncrasies to make accurate, target-specific emotion predictions. In both studies, participants predicted the emotion transitions of a specific target-either a close friend (Study 1) or a first-year college roommate (Study 2)-as well as an average group member. Results demonstrate that people can make highly accurate predictions both for specific individuals and specific groups. Accurate predictions rely on target-specific knowledge; new community members were able to make accurate predictions at zero-acquaintance, but accuracy increased over time as individuals accrued specialized knowledge. Results also suggest that accurate emotion prediction is associated with social success in both individual and communal relationships and that such a relation might emerge over time. Overall, our studies suggest that people accurately make individualized predictions of others' emotion transitions and that doing so fulfills a meaningful function in the social world. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

The Naïve Utility Calculus as a unified, quantitative framework for action understanding

The human ability to reason about the causes behind other people' behavior is critical for navigating the social world. Recent empirical research with both children and adults suggests that this ability is structured around an assumption that other agents act to maximize some notion of subjective utility. In this paper, we present a formal theory of this Naïve Utility Calculus as a probabilistic generative model, which highlights the role of cost and reward tradeoffs in a Bayesian framework for action-understanding. Our model predicts with quantitative accuracy how people infer agents' subjective costs and rewards based on their observable actions. By distinguishing between desires, goals, and intentions, the model extends to complex action scenarios unfolding over space and time in scenes with multiple objects and multiple action episodes. We contrast our account with simpler model variants and a set of special-case heuristics across a wide range of action-understanding tasks: inferring costs and rewards, making confidence judgments about relative costs and rewards, combining inferences from multiple events, predicting future behavior, inferring knowledge or ignorance, and reasoning about social goals. Our work sheds light on the basic representations and computations that structure our everyday ability to make sense of and navigate the social world.

Children's understanding of habitual behaviour

Research into the development of Theory of Mind (ToM) has shown how children from a very early age infer other people's goals. However, human behaviour is sometimes driven not by plans to achieve goals, but by habits, which are formed over long periods of reinforcement. Habitual and goal-directed behaviours are often aligned with one another but can diverge when the optimal behavioural policy changes without being directly reinforced (thus specifically hobbling the habitual learning strategy). Unlike the flexibility of goal-directed behaviour, rigid habits can cause agents to persist in behaviour that is no longer adaptive. In the current study, all children predict agents will tend to behave consistently with their goals, but between the ages of 5 and 10, children showed an increasing understanding of how habits can cause agents to persistently take suboptimal actions. These findings stand out from the typical way the development of social reasoning is examined, which instead focuses on children's increasing appreciation of how others' beliefs or expectations affect how they will act in service of their goals. The current findings show that children also learn that under certain circumstances, people's actions are suboptimal despite potentially 'knowing better.'

Rationalization: Why, when, and what for?

In this commentary, we ask when rationalization is most likely to occur and to not occur, and about where to expect, and how to measure, its benefits.

The Acquisition of Person Knowledge

How do we learn what we know about others? Answering this question requires understanding the perceptual mechanisms with which we recognize individuals and their actions, and the processes by which the resulting perceptual representations lead to inferences about people's mental states and traits. This review discusses recent behavioral, neural, and computational studies that have contributed to this broad research program, encompassing both social perception and social cognition.

Habit in Personality and Social Psychology

Habits are largely absent from modern social and personality psychology. This is due to outdated perspectives that placed habits in conflict with goals. In modern theorizing, habits are represented in memory as implicit context–response associations, and they guide responding in conjunction with goals. Habits thus have important implications for our field. Emerging research shows that habits are an important mechanism by which people self-regulate and achieve long-term goals. Also, habits change through specific interventions, such as changes in context cues. I speculate that understanding of habits also holds promise for reducing intergroup discrimination and for understanding lay theories of the causes for action. In short, by recognizing habit, the field gains understanding of a central mechanism by which actions persist in daily life.

Formalizing emotion concepts within a Bayesian model of theory of mind

Sensitivity to others' emotions is foundational for many aspects of human life, yet computational models do not currently approach the sensitivity and specificity of human emotion knowledge. Perception of isolated physical expressions largely supplies ambiguous, low-dimensional, and noisy information about others' emotional states. By contrast, observers attribute specific granular emotions to another person based on inferences of how she interprets (or 'appraises') external events in relation to her other mental states (goals, beliefs, moral values, costs). These attributions share neural mechanisms with other reasoning about minds. Situating emotion concepts in a formal model of people's intuitive theories about other minds is necessary to effectively capture humans' fine-grained emotion understanding.

Neuroanatomical correlates of forgiving unintentional harms

Mature moral judgments rely on the consideration of a perpetrator’s mental state as well as harmfulness of the outcomes produced. Prior work has focused primarily on the functional correlates of how intent information is neurally represented for moral judgments, but few studies have investigated whether individual differences in neuroanatomy can also explain variation in moral judgments. In the current study, we conducted voxel-based morphometry analyses to address this question. We found that local grey matter volume in the left anterior superior temporal sulcus, a region in the functionally defined theory of mind or mentalizing network, was associated with the degree to which participants relied on information about innocent intentions to forgive accidental harms. Our findings provide further support for the key role of mentalizing in the forgiveness of accidental harms and contribute preliminary evidence for the neuroanatomical basis of individual differences in moral judgments.