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4.2 Symbolic Cognitive Architectures
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4.2.2 ACT-R

In the grand scope of cognitive architectures, ACT-R is quite similar to Soar, but there are many micro-level differences. ACT-R is defined in terms of declarative and procedural knowledge, where procedural knowledge takes the form of Soar-like production rules, and declarative knowledge takes the form of chunks. It contains a variety of mechanisms for learning new rules and chunks from old; and also contains sophisticated probabilistic equations for updating the activation levels associated with items of knowledge (these equations being roughly analogous in function to, though quite different from, the ECAN equations in CogPrime).

Figure 4.2 displays the current architecture of ACT-R. The flow of cognition in the system is in response to the current goal, currently active information from declarative memory, information attended to in perceptual modules (vision and audition are implemented), and the current state of motor modules (hand and speech are implemented). The early work with ACT-R was based on comparing system performance to human behavior, using only behavioral measures, such as the timing of keystrokes or patterns of eye movements. Using such measures, it was not possible to test detailed assumptions about which modules were active in the performance of a task. More recently the ACT-R community has been engaged in a process of using imaging data to provide converging data on module activity. Figure 4.3 illustrates the associations they have made between the modules in Figure 4.2 and brain regions. Coordination among all of these components occurs through actions of the procedural module, which is mapped to the basal ganglia.

[Diagram Labels]
Intentional Module (not identified)
Declarative Module (Temporal/Hippocampus)
Goal Buffer (DLPFC)
Retrieval Buffer (VLPFC)
Matching (Striatum)
Selection (Pallidum)
Execution (Thalamus)
Visual Buffer (Parietal)
Manual Buffer (Motor)
Visual Module (Occipital/etc)
Manual Module (Motor/Cerebellum)
Environment

Fig. 4.2: High-level architecture of ACT-R

In practice ACT-R, even more so than Soar, seems to be used more as a programming framework for cognitive modeling than as an AI system. One can fairly easily use ACT-R to program models of specific human mental behaviors, which may then be matched against

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