Bayesian statistical methods provide a flexible and principled framework for relating cognitive models to behavioral data. They allow for cognitive models to be formalized, evaluated, and applied, supporting inferences about parameters, the testing of models, and making predictions about data. This chapter argues that Bayesian methods are most useful for cognitive modeling in allowing more ambi...

th This special issue of Cognitive Systems Research features the top twelve papers from the 4 International Conference on Cognitive Modeling (ICCM-2001). These papers represent the current trends in computational cognitive modeling, displaying both the diversity and commonalities of the field. This introduction to the special issue describes the motivations for the conference and the special is...

Knowledge engineering tools are becoming ever more complex, and therefore increased cognitive support will be necessary to leverage the potential of those tools. Our paper motivates this claim by examining some previous work in this domain and explaining the nature of cognitive support. We discuss some of the problem areas we have encountered in our research. Through user questionnaires and obs...

PDP++ is a freely available, open source software package designed to support the development, simulation, and analysis of research-grade connectionist models of cognitive processes. It supports most popular parallel distributed processing paradigms and artificial neural network architectures, and it also provides an implementation of the LEABRA computational cognitive neuroscience framework. M...

Modeling general intelligence has a long history: At the beginnings of AI, researchers searched for the general problem solving mechanism to model intelligence. While researchers failed to solve this complex problem, AI achieved great success when modeling cognitive abilities separately. In recent time a growing number of research endeavors aims again at human–level intelligence via integrating...

Cognitive modeling techniques provide a way of evaluating user interface designs, based on what is known about human cognitive strengths and limitations. Cognitive modelers face a tradeoff, however: more detailed models require disproportionately more time and effort to develop than coarser models. In this paper we describe a system, G2A, that automatically produces translations from abstract G...

This paper presents a formal approach to cognitive modeling by utilizing conceptual spaces. Conceptual spaces were introduced by Peter Gärdenfors as geometric and topologic representations that mediate between the symbolic and subconceptual cognitive levels. They can be used for knowledge representation and to explain cognitive reasoning. The goal here is to discuss both the advantages of this ...

The article first addresses the importance of cognitive modeling, in terms of its value to cognitive science (as well as other social and behavioral sciences). In particular, it emphasizes the use of cognitive architectures in this undertaking. Based on this approach, the article addresses, in detail, the idea of a multi-level approach that ranges from social to neural levels. In physical scien...

One of the major challenges associated with making compelling virtual worlds for computer games is populating them with intelligent characters. Most of today’s characters are mindless automatons that follow an inflexible set of simple rules. Unfortunately, when we start to make characters try and think for themselves we can run into difficulties. For example, if we are not extra careful about h...