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 is that there is a natural domain of (...) human functioning 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 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. (shrink)

In this lucid portrayal of human behavior, Fred Dretske provides an original account of the way reasons function in the causal explanation of behavior.

Frances Egan argues that the states of computational theories of vision are individuated individualistically and, as far as the theory is concerned, are not intentional. Her argument depends on equating the goals and explanatory strategies of computational psychology with those of its algorithmic level. However, closer inspection of computational psychology reveals that the computational level plays an essential role in explaining visual processes and that explanations at this level are nonindividualistic and intentional. In conclusion, I sketch an account of content (...) in which content does the sort of explanatory work that Egan denies is possible. (shrink)

The functionalist view of the nature of the mind is now widely accepted. Like behaviorism and physicalism, functionalism seeks to answer the question "What are mental states?" I shall be concerned with identity thesis formulations of functionalism. They say, for example, that pain is a functional state, just as identity thesis formulations of physicalism say that pain is a physical state.

According to historical theories of biological function, a trait's function is determined by natural selection in the past. I argue that, in addition to historical functions, ahistorical functions ought to be recognized. I propose a theory of biological function which accommodates both. The function of a trait is the way it contributes to fitness and fitness can only be determined relative to a selective regime. Therefore, the function of a trait can only be specified relative to a selective regime. Apart (...) from its desirable pluralism, only this view of relational function can support the function/accident and function/malfunction distinctions commonly thought to be part of the concept of function. Furthermore, only relational function correctly characterizes the explanatory consequences of function attributions in evolutionary biology. (shrink)