Research in computational cognitive modeling investigates the nature of cognition through developing process-based understanding by specifying computational models of mechanisms (including representations) and processes. In this enterprise, a cognitive architecture is a domaingeneric computational cognitive model that may be used for a broad, multiple-level, multipledomain analysis of behavior. It embodies generic descriptions of cognition in computer algorithms and programs. Developing cognitive architectures is a difficult but important task. In this article, discussions of issues and challenges in developing cognitive architectures will (...) be undertaken, and an example cognitive architecture (CLARION) will be described. (shrink)

One can often encounter claims that classical (Kolmogorovian) probability theory cannot handle, or even is contradicted by, certain empirical findings or substantive theories. This note joins several previous attempts to explain that these claims are unjustified, illustrating this on the issues of (non)existence of joint distributions, probabilities of ordered events, and additivity of probabilities. The specific focus of this note is on showing that the mistakes underlying these claims can be precluded by labeling all random variables involved contextually. Moreover, contextual (...) labeling also enables a valuable additional way of analyzing probabilistic aspects of empirical situations: determining whether the random variables involved form a contextual system, in the sense generalized from quantum mechanics. Thus, to the extent the Wang-Busemeyer QQ equality for the question order effect holds, the system describing them is noncontextual. The double-slit experiment and its behavioral analogues also turn out to form a noncontextual system, having the same probabilistic format (cyclic system of rank 4) as the one describing spins of two entangled electrons. (shrink)

It is shown that the Fodor's interpretation of the frame problem is the central indication that his version of the Modularity Thesis is incompatible with computationalism. Since computationalism is far more plausible than this thesis, the latter should be rejected.