The half-day tutorial introduces participants to the CLARION cognitive architecture and presents a detailed description, as well as simulation examples, advanced topics, and demonstrations. It will combine conceptual (psychological), theoretical, and implementation aspects of the architecture. Participants should have some prior exposure to cognitive architectures and artificial neural networks...

A standard model captures a community consensus over a coherent region of science, serving as a cumulative reference point for the field that can provide guidance for both research and applications, while also focusing efforts to extend or revise it. Here we propose developing such a model for humanlike minds, computational entities whose structures and processes are substantially similar to th...

Introduction This paper builds upon a study of how people find faults in a simple device and a corresponding cognitive model (Ritter & Bibby, 2008). This existing model, Diag, was implemented in Soar 6 and is based on the idea that learning consists of procedural, declarative, and episodic learning. Diag was developed to analyze human behavior while solving a simple diagrammatic problem (Ritter...

John R. Anderson is an international leader in the computational representation and simulation of human cognition. He is credited as having developed the first ‘‘cognitive architecture’’—a computational framework for specifying both the abilities and limitations of human behavior. Anderson has also made fundamental contributions in applying cognitive architectures to practical problems, most no...

The current study investigated whether cognitive architectures tuned to the magnitudes of nonsymbolic ratios support the acquisition of symbolic fraction concepts and subsequent achievement in algebra. Participants’ performance on a novel battery of nonsymbolic ratio comparison tasks predicted their symbolic fraction knowledge and algebra achievement even after controlling for performance on co...

their valuable comments and guidance.

Several distinctions between various concepts of context are discussed: internal vs. external, intrinsic vs. model-based, and implicit vs. explicit. F ina l ly , a dynamic theory of implicit, intrinsic, internal context is briefly discussed and its application to a context-sensitive general cognitive architecture DUAL and a context-sensitive model of human reasoning, AMBR, are

Of all the aspects differentiating lifelong learning from shorter-term, more specialized learning, perhaps none is more central than forgetting – or, to frame the issue more generally and technically, ”memory access speed deprioritization.” This extended abstract reviews some of the ideas involved in forgetting for lifelong learning systems, and briefly discusses the forgetting mechanisms used ...

Marco Polo describes a bridge, stone by stone. “But which is the stone that supports the bridge?” Kublai Khan asks. “The bridge is not supported by one stone or another,” Marco answers, “but by the line of the arch that they form.” Kublai Khan remains silent, reflecting. Then he adds: “Why do you speak to me of the stones? It is only the arch that matters to me.” Polo answers: “Without stones, ...

In this manuscript, we summarize the results of our research program aiming at describing the cognitive architecture underlying the representation of recursive hierarchical embedding. After conducting a series of behavioral and fMRI experiments in the visual, musical and motor domains, we found that, behaviorally, the acquisition of recursive rules seems supported by cognitive resources that ar...