This paper introduces a special issue of "Cognitive Science" initiated on the 25th anniversary of the publication of "Parallel Distributed Processing" (PDP), a two-volume work that introduced the use of neural network models as vehicles for understanding cognition. The collection surveys the core commitments of the PDP…

There is a crucial debate concerning the nature of chess chunks: One current possibility states that chunks are built by encoding particular combinations of pieces-on-squares (POSs), and that chunks are formed mostly by "close" pieces (in a "Euclidean" sense). A complementary hypothesis is that chunks are encoded by abstract,…

Recent models of the conceptual system hold that concepts are grounded in simulations of actual experiences with instances of those concepts in sensory-motor systems (e.g., Barsalou, 1999, 2003; Solomon & Barsalou, 2001). Studies supportive of such a view have shown that verifying a property of a concept in one modality, and then switching to…

The remarkable successes of the physical sciences have been built on highly general quantitative laws, which serve as the basis for understanding an enormous variety of specific physical systems. How far is it possible to construct universal principles in the cognitive sciences, in terms of which specific aspects of perception, memory, or decision…

Previous reports have demonstrated that the comprehension of sentences describing motion in a particular direction (toward, away, up, or down) is affected by concurrently viewing a stimulus that depicts motion in the same or opposite direction. We report 3 experiments that extend our understanding of the relation between perception and language…

This article presents a formal theory of robot perception as a form of abduction. The theory pins down the process whereby low-level sensor data is transformed into a symbolic representation of the external world, drawing together aspects such as incompleteness, top-down information flow, active perception, attention, and sensor fusion in a…

The natural input memory (NAM) model is a new model for recognition memory that operates on natural visual input. A biologically informed perceptual preprocessing method takes local samples (eye fixations) from a natural image and translates these into a feature-vector representation. During recognition, the model compares incoming preprocessed…

What the participants share, their common "sense" of the world, creates a foundation, a framing, an orientation that enables human actors to see and act in coordination with one another. For recurrent activities, the methods the participants use to understand each other as they act change, making the intersubjective space in which actors operate…