Theory of Minds: Early Understanding of Interacting Minds

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Annual Review of Developmental Psychology
Theory of Minds:
Early Understanding of
Interacting Minds
Aaron Chuey and Hyowon Gweon
Department of Psychology, Stanford University, Stanford, California, USA;
email: [email protected], [email protected]
Annu. Rev. Dev. Psychol. 2025. 7:91–115
The Annual Review of Developmental Psychology is
online at devpsych.annualreviews.org
https://doi.org/10.1146/annurev-devpsych-111323-
115032
Copyright © 2025 by the author(s). This work is
licensed under a Creative Commons Attribution 4.0
International License, which permits unrestricted
use, distribution, and reproduction in any medium,
provided the original author and source are credited.
See credit lines of images or other third-party
material in this article for license information.
Keywords
Theory of Mind, communication, social cognition, cognitive development,
social learning
Abstract
The idea that we understand others’ actions in terms of their underlying
mental states has shaped decades of developmental research on social cog-
nition. Existing work, however, has primarily focused on reasoning about
the minds of isolated individuals, leaving open questions about how we
reason about the minds of interacting individuals. In fact, children rou-
tinely observe social interactions well before they themselves can interact
with others; how do children make sense of these observations? We pro-
pose that humans, starting early in life, can extend their understanding
of individual minds (Theory of Mind) to encompass the causal relation-
ship between multiple agents’ minds and actions (Theory of Minds). We
ground our proposal within existing computational frameworks that con-
sider mental-state reasoning as a core component of action understanding,
communication, and social learning. We then review empirical work that ex-
amines children’s emerging understanding of interacting minds and discuss
its development. We close by suggesting directions for future work toward
a unied description of how humans make sense of their complex social
environment.
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Contents
1. INTRODUCTION........................................................... 92
2. THEORY OF MIND: AN UNDERSTANDING OF INDIVIDUAL MINDS . . . 94
2.1. Computational Models of Theory of Mind . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
2.2. DevelopmentofTheoryofMind.......................................... 95
3. MENTAL-STATE REASONING AND COMMUNICATION . . . . . . . . . . . . . . . . . 97
3.1. Computational Models of Communicative Inference . . . . . . . . . . . . . . . . . . . . . . . . 97
3.2. Development of Communicative Inference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98
4. THEORY OF MINDS: AN UNDERSTANDING OF HOW MINDS
INTERACT................................................................... 100
4.1. FormalFramework........................................................ 100
4.2. DevelopmentofTheoryofMinds.......................................... 101
4.3. PossibleMediators........................................................ 104
5. OPEN QUESTIONS AND FUTURE DIRECTIONS . . . . . . . . . . . . . . . . . . . . . . . . . 106
5.1. Beyond One-Shot, Dyadic Interactions: Social Relationships
andNetworks............................................................. 106
5.2. Beyond Real-Time Communication: Exploring Different Channels
forSocialInuence........................................................ 107
5.3. Beyond Cooperative Communication: Reasoning About Adversarial
Interactions............................................................... 107
5.4. BeyondTheoryofMindsinHumans....................................... 108
6. CONCLUSION............................................................... 108
1. INTRODUCTION
Human social cognition is mentalistic at its core: We cannot help but think about others’ behaviors
in terms of what is going on inside their minds. For example, when we see a man running toward
a train in a busy train station, we can easily entertain various internal states that might underlie his
behavior, ranging from his perception (he sees or hears a train arriving),desires (he wants to get on
that train), beliefs (he thinks the train will leave soon), and emotions (he might feel anxious about
being late to work). This example illustrates a powerful idea that has shaped decades of research
on human cognition: By representing and attributing unobservable mental states to observable
behaviors, humans can predict, explain, and even intervene on others’ behaviors. Critically, the
systematicity and exibility by which we reason about other minds suggests that we, as humans,
have a theory-like understanding of others’ mental states that is both causal and abstract: a Theory
of Mind (ToM) (Premack & Woodruff 1978, Wellman 2018).
On the one hand, research on ToM has been a remarkably productive enterprise. A range
of experimental paradigms have been designed to study mental-state reasoning in young chil-
dren (e.g., Baron-Cohen et al. 1985, Buttelmann et al. 2009, Gopnik & Astington 1988, Onishi
& Baillargeon 2005, Wellman & Liu 2004, Wimmer & Perner 1983), shedding light on its de-
velopment (see Rakoczy 2022), its universality and variability across cultures (e.g., Barrett & Saxe
2021, Barrett et al. 2013, Liu et al. 2008), and the differences and similarities between humans and
other species (see Call & Tomasello 2008, Martin & Santos 2016, Royka & Santos 2022). On the
other hand, this literature has been mostly constrained to studying how children reason about the
minds of individual agents and, in particular, agents whose mental states are shaped only by their
rsthand experience with the world. By investigating early social reasoning using these rather
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asocial scenarios, previous work may have overlooked a crucial function of social cognition:
understanding the interactions between other people.
Humans constantly communicate, cooperate, and compete within complex social networks.
Through these connections, people’s minds and actions become inextricably linked to those of
others. Naturally, when we think about someone’s mind, we often consider how it might shape (or
be shaped by) others. For instance, what if the man in the above example starts running toward
a different train after a woman says something to him? Our mind naturally goes to what might
explain her behavior and how it could have inuenced the man’s: Perhaps she knew where the
man was headed, believed he was going to board the wrong train, and intervened as a prosocial
bystander. Regardless of the exact reason behind the man’s change in course, we cannot help but
think that it must have been caused by the woman’s beliefs and desires.
Studying how humans interact with others has been a longstanding direction in social psy-
chology, and recent proposals have called for a renewed interest in studying the cognitive
underpinnings of such interactions (e.g., Wheatley et al. 2024). The focus of the current review
is on a related yet distinct inferential challenge: how humans—as observers—think about others’
interactions. Drawing on the idea that humans reason about other minds using an intuitive theory
of individual minds (i.e., ToM), we propose that reasoning about the interaction between multiple
minds is also supported by an intuitive theory: a Theory of Minds (ToMS).
At rst glance, one might wonder whether having a ToMS simply means applying ToM to
more than one agent at a time or whether there is any utility in conceptualizing ToMS as a dis-
tinct construct. Yet, understanding others’ interactions requires more than representing the minds
of isolated individuals; it involves reasoning about agents who can think about and inuence each
other’s minds, particularly through acts of communication. Thus, while ToMS might be a natural
extension of ToM, it is still useful to distinguish the two (see Figure 1). Our goal here is to char-
acterize ToMS and the inferences it enables so that we can ask more precise empirical questions
about how young children understand the dynamics of their expanding social environment.
We focus on two methodological approaches that have advanced our scientic understanding of
how humans reason about other minds.1One approach is to build computational models that for-
malize social reasoning; by making explicit commitments about the representations and inferential
processes that underlie our everyday intuitions, cognitive models help distill complex reasoning
into its core components. Particularly successful endeavors come from the broader tradition of
characterizing human cognition as Bayesian inference operating over abstract, structured repre-
sentations (Tenenbaum et al.2011).This framework has been productively applied to explain many
aspects of social reasoning, such as reasoning about others’ desires and beliefs (Baker et al. 2009,
2017; Jara-Ettinger 2019; Lucas et al. 2014), emotions (Houlihan et al. 2023,Ong et al. 2015, Saxe
& Houlihan 2017, Wu et al. 2021), and dynamic cognitive processes (e.g., memory and attention;
see Rubio-Fernandez et al. 2024). Another approach is to conduct empirical studies that examine
mental-state reasoning in specic populations, such as children (e.g., Rakoczy 2022), nonhuman
primates (e.g., Drayton & Santos 2018, Krupenye & Call 2019, Tomasello 2023), and people who
have atypical perceptual or cognitive faculties (e.g., Baron-Cohen 2000; Pyers & de Villiers 2013;
Richardson et al. 2020, 2023). In particular, over the past few decades, researchers have developed
ingenious experimental paradigms to systematically probe infants’ and young children’s reasoning
about other minds. By revealing striking successes and failures in their early understanding of the
social world (see Wellman 2017), this literature has advanced our understanding of how social
1While this review focuses on computational and behavioral work,we acknowledge that other methods, such as
neuroimaging, have made signicant contributions to the eld (see Gweon & Saxe 2013, Koster-Hale & Saxe
2013); for a brief discussion of how neuroimaging might inform our understanding of ToMS, see Section 5.
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Perception
Beliefs
Desires
AGENT
Action
OBSERVER
Theory of Mind (ToM)
COMMUNICATOR RECIPIENT
OBSERVER
Theory of Minds (ToMS)
Action
Perception Beliefs
Desires
PerceptionBeliefs
Desires
Action
Figure 1
Schematics of (top) Theory of Mind (ToM) and (bottom) Theory of Minds (ToMS) from an observer’s perspective. (Top) In ToM, an
observer reasons about the mind of a single agent who acquires information from the environment: The agent uses information
gathered from their perception (e.g., vision) to update their representation of the world (beliefs) and generates actions jointly on the
basis of their beliefs and desires. Executing an action changes the state of the world, yielding new information. (Bottom) In ToMS, two
agents (communicator and recipient) each possess the same mental capacities but can also represent each other’s minds (such as their
beliefs and desires) and can act in order to inuence the state of each other’s mental states and behaviors. For instance, when we
(observer) see a man running toward one train but then change course toward another train after a woman speaks to him, we can readily
reason about both agents’ beliefs about the world and about each other: Perhaps the man had a false belief about which train to catch,
the woman knew the right train, and she intervened to correct his false belief.
cognition develops in the rst few years of life. These two approaches are complementary in na-
ture. Computational models describe the structure of key representations involved in mental-state
inference in precise, quantitative terms, while developmental experiments characterize how these
representations emerge, change, and support early social reasoning.
In this review, we draw on these two lines of prior work to describe ToMS and its develop-
ment. Rather than providing an exhaustive survey of both literatures, we use formal models of
mental-state reasoning to ground and focus our review of the developmental literature. We start
by reviewing existing computational and developmental work on key components of ToMS: rea-
soning about an individual agent’s mind (i.e., ToM; see Section 2) and reasoning about another
agent in communicative contexts (Section 3). Then, we synthesize these perspectives to build a
framework for understanding how humans reason about interactions between minds and review
an emerging body of work that examines the development of these abilities (ToMS; see Section 4).
Finally, we discuss implications of this framework for cognitive development and new directions
for future work (Section 5), followed by concluding remarks (Section 6).
2. THEORY OF MIND: AN UNDERSTANDING OF INDIVIDUAL MINDS
Reasoning about the relationship between multiple minds necessarily depends on the ability to
represent the contents of an individual mind. In this section, we rst discuss key features of
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ToM within the context of formal models, followed by a brief survey of relevant developmental
literature.
2.1. Computational Models of Theory of Mind
ToM is a causal model of how unobservable mental states give rise to observable behaviors. Go-
ing back to the train station example, we understand that the observable aspects of the man’s
behavior—his gaze, actions, and even facial expressions—are caused by his internal states such as
his perceptions, desires, beliefs, goals, and emotions. By characterizing ToM as an intuitive theory,
or a model, of how another agent’s mental states cause their behaviors, ToM supports predictions
about how someone will behave given certain mental states (forward inference) as well as expla-
nations of someone’s behavior in terms of their underlying mental states (inverse inference). As
a rst step toward modeling human social cognition, Bayesian Theory of Mind (BToM) models
have formalized how people reason about others’ actions in terms of their underlying beliefs and
desires (e.g., Baker et al. 2009, 2017; but see also computational models that incorporate emotion
understanding, e.g., Houlihan et al. 2023, Ong et al. 2015, Wu et al. 2018).
At its core, BToM characterizes the underlying process by which humans expect agents to
(a) update their beliefs on the basis of new information gathered via perception and (b) generate
actions using a utility-maximizing sampling process. In this model, an agent with a desired goal
(e.g., getting to a particular location in a 2D grid world) acquires perceptual information from
the world and rationally updates their beliefs about the state of the world using Bayes’ rule. The
agent generates actions (e.g., moving one step closer to the goal) based jointly on their beliefs and
desires, a process operationalized as a reward function that assigns positive (reward) and negative
(cost) utility to possible world states (i.e., the spatial location of the agent with respect to the goal).
The agent is assumed to be rational, selecting actions that maximize their expected utility given
their beliefs. Executing an action (e.g., moving one step) alters the current state of the world,
leading the agent to acquire new information, update their beliefs, and plan subsequent actions.
Modeling agents as utility-maximizing action planners supports both forward inferences about
their future actions and inverse inferences about their underlying mental states. Running the
model forward with a set of mental states produces actions the agent will take to maximize their
expected utility (e.g., a man who wants to travel to Chicago will approach the Chicago-bound
train). Inverting the model given the agent’s actions recovers the mental states that would have
led the agent to select those actions (e.g., a man approaching the Chicago-bound train probably
wants to go to Chicago). Indeed, BToM can explain adults’ inferences in both directions: predict-
ing an agent’s movement given their beliefs and desires and jointly inferring beliefs and desires
from an agent’s motion trajectory (Baker et al. 2017).
Overall, BToM species the internal causal structure that we attribute to other agents—
percepts, desires, and beliefs—and how it gives rise to observable actions. As we review below,
decades of empirical literature on the development of ToM suggest that while key aspects of ToM
are present early in life, they also undergo substantial developmental change.
2.2. Development of Theory of Mind
One of the simplest internal structures we can attribute to an agent’s mind is the connection
between perception, goals, and observable actions (Baker et al. 2009). The earliest evidence for
such an understanding comes from violation of expectation paradigms that examine infants’
looking time in response to unexpected events (Margoni et al. 2023); these measures reect a
kind of forward inference, which involves predicting what an agent will do given preceding events
that inuenced their mental states and reacting to the discrepancy between the predicted and
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