Computation and cognition: issues in the foundations of cognitive science

Computation and cognition: issues in the foundations of cognitive science

Abstract: The computational view of mind rests on certain intuitions regarding the fundamental similarity between computation and cognition. We examine some of these intuitions and suggest that they derive from the fact that computers and human organisms are both physical systems whose behavior is correctly described as being governed by rules acting on symbolic representations. Some of the implications of this view are discussed. It is suggested that a fundamental hypothesis of this approach (the "proprietary vocabulary hypothesis") is that there is a natural domain of human functioning (roughly what we intuitively associate with perceiving, reasoning, and acting) that can be addressed exclusively in terms of a formal symbolic or algorithmic vocabulary or level of analysis.

Much of the paper elaborates various conditions that need to be met if a literal view of mental activity as computation is to serve as the basis for explanatory theories. The coherence of such a view depends on there being a principled distinction between functions whose explanation requires that we posit internal representations and those that we can appropriately describe as merely instantiating causal physical or biological laws. In this paper the distinction is empirically grounded in a methodological criterion called the "cognitive impenetrability condition." Functions are said to be cognitively impenetrable if they cannot be influenced by such purely cognitive factors as goals, beliefs, inferences, tacit knowledge, and so on. Such a criterion makes it possible to empirically separate the fixed capacities of mind (called its "functional architecture") from the particular representations and algorithms used on specific occasions. In order for computational theories to avoid being ad hoc, they must deal effectively with the "degrees of freedom" problem by constraining the extent to which they can be arbitrarily adjusted post hoc to fit some particular set of observations. This in turn requires that the fixed architectural function and the algorithms be independently validated. It is argued that the architectural assumptions implicit in many contemporary models run afoul of the cognitive impenetrability condition, since the required fixed functions are demonstrably sensitive to tacit knowledge and goals. The paper concludes with some tactical suggestions for the development of computational cognitive theories.

One. Introduction and summary

The view that cognition can be understood as computation is ubiquitous in modern cognitive theorizing, even among those who do not use computer programs to express models of cognitive processes. One of the basic assumptions behind this approach, sometimes referred to as "information processing psychology," is that cognitive processes can be understood in terms of formal operations carried out on symbol structures. It thus represents a formalist approach to theoretical explanation. In practice, tokens of symbol structures may be depicted as expressions written in some lexicographic notation (as is usual in linguistics or mathematics), or they may be physically instantiated in a computer as a data structure or an executable program.

The "information processing" idiom has been with us for about two decades and represents a substantial intellectual commitment among students of cognition. The fields that share this view (notably, segments of linguistics, philosophy of mind, psychology, artificial intelligence, cultural anthropology, and others) have been increasingly looking toward some convergence as the "cognitive sciences." Several journals devoted to that topic now exist (including, to some extent, BBS), and a Cognitive Science Society has just been formed. There remains, however, considerable uncertainty regarding precisely what constitutes the core of the approach and what constraints it imposes on theory construction.

In this essay I shall present what I consider some of the crucial characteristics of the computational view of mind and defend them as appropriate for the task of explaining cognition. As in the early stages of many scientific endeavors, the core of the approach is implicit in scientists' intuitions about what are to count as relevant phenomena and as legitimate explanations of the underlying processes. Yet as we tease out the central assumptions, we will find room for refinement: not everything that is intuitively cognitive will remain so as the theory develops, nor will all processes turn out to be appropriate for explaining cognitive phenomena.

We begin with an informal discussion of the position that certain types of human behavior are determined by representations (beliefs, tacit knowledge, goals, and so on). This, we suggest, is precisely what recommends the view that mental activity is computational. Then we present one of the main empirical claims of the approach - namely, that there is a natural domain of inquiry that can be addressed at a privileged algorithmic level of analysis, or with a proprietary vocabulary.

The remainder of the paper elaborates various requirements for constructing adequate explanatory theories on this basis. First, however, we need to analyse the notions of