The goal of building cognitive architectures is to achieve an understanding of mental processes by constructing testable information processing models.

Cognitive architectures are... Leibnizian machines... designed to bring forth the feats of cognition, and built to allow us to enter... examine them, and to watch their individual parts... pushing and pulling... thereby explaining how a mind works.

A cognitive architecture specifies aspects of an intelligent system that are stable over time, much as in a building’s architecture. These include the memories that store perceptions, beliefs, and knowledge, the representation of elements that are contained in these memories, the performance mechanisms that use them, and the learning processes that build on them. Such a framework typically comes with a programming language and software environment that supports the efficient construction of knowledge-based systems.

Research on cognitive architectures varies widely in the degree to which it attempts to match psychological data. ACT-R (Anderson & Lebiere, 1998) and EPIC (Kieras & Meyer, 1997) aim for quantitative fits to reaction time and error data, whereas Prodigy (Minton et al., 1989) incorporates selected mechanisms like means-ends analysis but otherwise makes little contact with human behavior. Architectures like Soar (Laird, Newell, & Rosenbloom, 1987; Newell, 1990) and Icarus (Langley & Choi, in press; Langley & Rogers, 2005) take a middle position, drawing on many psychological ideas but also emphasizing their strength as flexible AI systems. What they hold in common is an acknowledgement of their debt to theoretical concepts from cognitive psychology and a concern with the same intellectual abilities as humans.

This book is an attempt to explain cognition—thought, perception, emotion, experience—in terms of a machine, that is, using a cognitive architecture.

When taken as a way of modeling cognitive architecture, really does represent an approach that is quite different from that of the classical cognitive science that it seeks to replace. Classical models of the mind were derived from the structure of Turing and Von Neumann machines. They are not, of course, committed to the details of these machines as exemplified in Turing's original formulation or in typical commercial computers—only to the basic idea that the kind of computing that is relevant to understanding cognition involves operations on symbols.. In contrast, connectionists propose to design systems that can exhibit intelligent behavior without storing, retrieving, or otherwise operating on structured symbolic expressions. The style of processing carried out in such models is thus strikingly unlike what goes on when conventional machines are computing some function.

When taken as a way of modeling cognitive architecture, really does represent an approach that is quite different from that of the classical cognitive science that it seeks to replace. Classical models of the mind were derived from the structure of Turing and Von Neumann machines. They are not, of course, committed to the details of these machines as exemplified in Turing's original formulation or in typical commercial computers—only to the basic idea that the kind of computing that is relevant to understanding cognition involves operations on symbols.. In contrast, connectionists propose to design systems that can exhibit intelligent behavior without storing, retrieving, or otherwise operating on structured symbolic expressions. The style of processing carried out in such models is thus strikingly unlike what goes on when conventional machines are computing some function.

Our... cognitive architecture is based on a formal [psychological] theory... the PSI theory... [which] has been turned into a computational model... MicroPSI... partially implemented as a computer program.

In cognitive science, we currently have two major families of architectures... One, the classical school... characterized as Fodorian Architectures, as... the manipulation of a language of thought, usually expressed as a set of rules and capable of . ...The other family favors distributed approaches and constrains a dynamic system with potentially astronomically many until... behaviors [of] general intelligence are left. This may seem more "natural" and well-tuned... Yet many functional aspects of intelligence... as planning and language, are... much harder to depict using the dynamical systems approach.

has been designed to provide guidelines intended to assist in the presentation of information in a manner that encourages learner activities that optimize intellectual performance. The theory assumes a limited capacity working memory that includes partially independent subcomponents to deal with auditory/verbal material and visual/2- or 3-dimensional information as well as an effectively unlimited long-term memory, holding schemas that vary in their degree of automation. These structures and functions of human cognitive architecture have been used to design a variety of novel instructional procedures based on the assumption that working memory load should be reduced and schema construction encouraged. This paper reviews the theory and the instructional designs generated by it.

Just as the extensive theoretical bodies of physics, chemistry, [etc.]... unified theories of cognition are not isolated statements discarded when... predictions [are] refuted. Rather they are paradigms... that direct a research program...

I propose that what we call “consciousness” is a feeling forming a backdrop to, or attached to, a current mental event or instinct. It is best grasped by considering a common engineering architecture called layering, which allows complex systems to function efficiently and in an integrated fashion, from atoms to molecules, to cells, to circuits, to cognitive and perceptual capacities. If the brain indeed consists of different layers (in the engineering sense), then information from a micro level may be integrated at higher and higher layers until each modular unit itself produces consciousness. A layer architecture allows for new levels of functioning to arise from lower-level functioning parts that could not create the “higher level” experience alone. It is time to learn more about layering and the wonders it brings to understanding brain architecture. We are on the road to realizing that consciousness is not a “thing.” It is the result of a process embedded in an architecture, just as a democracy is not a thing but the result of a process.

[W]e are in need of functionalist architectures. That is, we need to make explicit what entities we are going to research, what constitutes these entities conceptually, and how we may capture these concepts.

Seeing our common-sense conceptual framework for mental phenomena as a theory brings a simple and unifying organization to most of the major topics in the philosophy of mind.