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Hybrid Modeling of Cognition: Review of The Atomic Components of Thought. John R. Anderson and Christian J. Lebiere. Mahwah, NJ: Erlbaum, 1998

The Atomic Components of Thought (Anderson & Lebiere, 1998) is a report on an ambitious work in progress. As with most attempts to construct a unified theory of cognition this project harkens to the call of Allen Newell (1990) when he said: ‘‘Psychology has arrived at the possibility of unified theories of cognition—theories that gain their power by positing a single system of mechanisms that operate together to produce the full range of human cognition.’’ This is certainly the goal of Anderson and Lebiere and the ACT-R (Adaptive Components of Thought—Rational) team at Carnegie Mellon. In pursuing this goal, Anderson and his colleagues have constructed one of the most fully articulated and complex hybrid production rule architectures extant. They describe it as a hybrid architecture because it blends aspects of production rule modeling (conditional action rules interacting with a data structure) with a certain amount of subsymbolic processing (such as a memory activation function) similar to connectionist modeling. The latest version of this theory, ACT-R 4.0, allows finer grained modeling of thought and has clearer differentiation between symbolic and subsymbolic processes than previous ACT theories. ACT-R 4.0 is the subject of The Atomic Components of Thought. In the introduction to this book, Anderson and Lebiere present a ‘‘no-magic doctrine’’ consisting of six principles that they claim have driven their work with ACT-R and its realization in this book. These six principles can be taken as a benchmark from which they believe their work with the ACT-R theory should be measured. These principles do provide a good basis from which to evaluate their work. The first of these six principles insists that ACT-R remains experimentally grounded. Because psychology and cognitive science are attempts to describe reality, this is a necessity, and the authors do well in this arena with some small caveats. The book’s examples all carefully compare the performance of the ACT-R model with the performance of actual subjects, for example. More importantly though, this book, in Chapters 5 and 6, carefully explains the new work with ACT-RPM, an expansion of their model that includes a visual interface, auditory processing, speech production, and motor processing. These new features bring ACT-R a long way toward being more firmly grounded in the experimental data and are utilized in some of the models described later in the work. One could hope that at some point all