An Analogical Model of Pretense.

We argue that pretense can be viewed as analogical projection: a structural comparison between the pretend scenario and its real-world counterpart that leads to inferences about the pretend scenario. For example, in pretending to make a phone call with a banana, a number pad might be projected on the banana's surface. We model two empirical studies of early childhood pretense, and show how successful pretense requires making and accepting such inferences, while failed pretense can be traced to failure of such projection.

Expanding and Repositioning Cognitive Science.

Cognitive science has converged in many ways with cognitive psychology, but while also maintaining a distinctive interdisciplinary nature. Here we further characterize this existing state of the field before proposing how it might be reconceptualized toward a broader and more distinct, and thus more stable, position in the realm of sciences.

Evidence from machines that learn and think like people.

We agree with Lake et al.'s trenchant analysis of deep learning systems, including that they are highly brittle and that they need vastly more examples than do people. We also agree that human cognition relies heavily on structured relational representations.

Representation and Computation in Cognitive Models.

One of the central issues in cognitive science is the nature of human representations. We argue that symbolic representations are essential for capturing human cognitive capabilities. We start by examining some common misconceptions found in discussions of representations and models.

The Cognitive Science of Sketch Worksheets.

Computational modeling of sketch understanding is interesting both scientifically and for creating systems that interact with people more naturally. Scientifically, understanding sketches requires modeling aspects of visual processing, spatial representations, and conceptual knowledge in an integrated way. Software that can understand sketches is starting to be used in classrooms, and it could have a potentially revolutionary impact as the models and technologies become more advanced.

Extending SME to Handle Large-Scale Cognitive Modeling.

Analogy and similarity are central phenomena in human cognition, involved in processes ranging from visual perception to conceptual change. To capture this centrality requires that a model of comparison must be able to integrate with other processes and handle the size and complexity of the representations required by the tasks being modeled. This paper describes extensions to Structure-Mapping Engine (SME) since its inception in 1986 that have increased its scope of operation.

Vision and sketching.

This essay reflects on the revolution David Marr brought about in vision research, and in cognitive science more broadly. I start with an insider's view, then examine the methodological impact of his framework in cognitive science in general. My group's work on sketch understanding descends from Marr's approach to vision, a connection which I make to provide a concrete illustration.

Qualitative modeling.

Qualitative modeling concerns the representations and reasoning that people use to understand continuous aspects of the world. Qualitative models formalize everyday notions of causality and provide accounts of how to ground symbolic, relational representations in perceptual processes. This article surveys the basic ideas of qualitative modeling and their applications from a cognitive science perspective.

Computational models of analogy.

Analogical mapping is a core process in human cognition. A number of valuable computational models of analogy have been created, capturing aspects of how people compare representations, retrieve potential analogs from memory, and learn from the results. In the past 25 years, this area has progressed rapidly, fueled by strong collaboration between psychologists and Artificial Intelligence (AI) scientists, with contributions from linguists and philosophers as well.

AI and cognitive science: the past and next 30 years.

Artificial Intelligence (AI) is a core area of Cognitive Science, yet today few AI researchers attend the Cognitive Science Society meetings. This essay examines why, how AI has changed over the last 30 years, and some emerging areas of potential interest where AI and the Society can go together in the next 30 years, if they choose.

Reviving inert knowledge: analogical abstraction supports relational retrieval of past events.

We present five experiments and simulation studies to establish late analogical abstraction as a new psychological phenomenon: Schema abstraction from analogical examples can revive otherwise inert knowledge. We find that comparing two analogous examples of negotiations at recall time promotes retrieving analogical matches stored in memory-a notoriously elusive effect. Another innovation in this research is that we show parallel effects for real-life autobiographical memory (Experiments 1-3) and for a controlled memory set (Experiments 4 and 5).