Publications

Deciding to undergo a transformative experience present unique challenges for a reasonable decision-maker, and for any attempt to give …

We are surprised when events violate our intuitive physical expectations. Even infants look longer when things seem to magically …

When we reason about the goals of others, how do we balance the positive outcomes that actions led to, with the potentially bad ways …

People make fast, spontaneous, and consistent judgements of social situations, even in complex physical contexts with multiple-body …

Humans have an intuitive understanding of physics. They can predict how a physical scene will unfold, and reason about how it came to …

Cushman’s rationalization account can be extended to cover another part of his portrayal of representational exchange: thought …

From infancy, humans have expectations about how objects will move and interact. Even young children expect objects not to move through …

In this commentary we engage with Paul’s Transformative Experience as it relates to decision making. We consider why deciding whether …

Drawing together the metaphysics of counterfactuals with empirical work on intuitive judgments, this chapter discusses the nature of …

Constructing an intuitive theory from data confronts learners with a “chicken‐and‐egg” problem: The laws can only be expressed in terms …

Our everyday decisions are driven by costs, risk, and reward. How do people take these factors into account when they predict and …

People spend much of their time in imaginary worlds, and have beliefs about the events that are likely in those worlds, and the laws …

How do people hold others responsible for the consequences of their actions? We propose a computational model that attributes …

We introduce the Minimal Turing Test, an experimental paradigm for studying perceptions and meta-perceptions of different social groups …

Infants understand that people pursue goals, but how do they learn which goals people prefer? We tested whether infants solve this …

We were encouraged by the broad enthusiasm for building machines that learn and think in more human-like ways. Many commentators saw …

Humans acquire their most basic physical concepts early in development, and continue to enrich and expand their intuitive physics …

Languages commonly use physical properties to discuss non-physical states and events in the world. We investigate the degree to which …

Searching natural environments, as for example, when foraging or looking for a landmark, combines reasoning under uncertainty, planning …

Infants understand that people act in order to achieve their goals, but how can they tell what goals people find worthwhile? Here, we …

We explore the hypothesis that many intuitive physical inferences are based on a mental physics engine that is analogous in many ways …

We present the Neural Physics Engine (NPE), a framework for learning simulators of intuitive physics that naturally generalize across …

Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances …

How do people understand the pragmatics of spatial language? We propose a rational-speech act model for spatial reasoning, and apply it …

People have a common-sense notion of intelligence and use it to evaluate decisions and decision-makers. One can attribute intelligence …

Models of learning concepts or theories often invoke a stochastic search process, in which learners generate hypotheses through some …

his thesis develops formal computational models of intuitive theories, in particular intuitive physics and intuitive psychology, which …

In order to be held responsible, a person’s action has to have made some sort of difference to the outcome. In this paper, we …

Humans acquire their most basic physical concepts early in development, but continue to enrich and expand their intuitive physics …

An intuitive theory is a system of abstract concepts and laws relating those concepts that together provide a framework for explaining …

We present an algorithmic model for the development of children’s intuitive theories within a hierarchical Bayesian framework, …

We consider an approach to blame attribution based on counterfactual reasoning in probabilistic generative models. In this view, people …

Evaluating individuals based on their pro- and anti-social behaviors is fundamental to successful human interaction. Recent research …

The very early appearance of abstract knowledge is often taken as evidence for innateness. We explore the relative learning speeds of …

Everyday social interactions are heavily influenced by our snap judgments about others goals. Even young infants can infer the goals of …

We consider causality as a domain-general intuitive theory and ask whether this intuitive theory can be learned from cooccurrence of …