Editing ACT-R (section)

===The symbolic vs. connectionist debate===
In the [[cognitive science]]s, different theories are usually ascribed to either the "[[Cognitivism (psychology)|symbolic]]" or the "[[connectionism|connectionist]]" approach to cognition. ACT-R clearly belongs to the "symbolic" field and is classified as such in standard textbooks and collections.<ref>{{cite book |first=T. A.|last=Polk|author2=C. M. Seifert|year=2002|title=Cognitive Modeling|publisher=MIT Press|location=Cambridge, Massachusetts|isbn=0-262-66116-0}}</ref> Its entities (chunks and productions) are discrete and its operations are syntactical, that is, not referring to the semantic content of the representations but only to their properties that deem them appropriate to participate in the computation(s). This is seen clearly in the chunk slots and in the properties of buffer matching in productions, both of which function as standard symbolic variables.

Members of the ACT-R community, including its developers, prefer to think of ACT-R as a general framework that specifies how the brain is organized, and how its organization gives birth to what is perceived (and, in cognitive psychology, investigated) as mind, going beyond the traditional symbolic/connectionist debate. None of this, naturally, argues against the classification of ACT-R as symbolic system, because all symbolic approaches to cognition aim to describe the mind, as a product of brain function, using a certain class of entities and systems to achieve that goal.

A common misunderstanding suggests that ACT-R may not be a symbolic system because it attempts to characterize brain function. This is incorrect on two counts: First, all approaches to computational modeling of cognition, symbolic or otherwise, must in some respect characterize brain function, because the mind is brain function. And second, all such approaches, including connectionist approaches, attempt to characterize the mind at a cognitive level of description and not at the neural level, because it is only at the cognitive level that important generalizations can be retained.<ref>Pylyshyn, Z. W. (1984). ''Computation and Cognition: Toward a Foundation for Cognitive Science''. Cambridge, Massachusetts: MIT Press.  {{ISBN|0-262-66058-X}}.</ref>

Further misunderstandings arise because of the associative character of certain ACT-R properties, such as chunks spreading activation to each other, or chunks and productions carrying quantitative properties relevant to their selection. None of these properties counter the fundamental nature of these entities as symbolic, regardless of their role in unit selection and, ultimately, in computation.