According to this view, linguistic symbols are external to the cognitive system and what the system must learn to do is produce and comprehend such symbols. In this paper I pursue that idea by arguing that ability in natural deduction itself may rely on pattern recognition abilities that enable us to operate on external symbols rather than encodings of rules that might be applied to internal representations. To support this suggestion, I present a series of experiments with connectionist networks that have been trained to construct simple natural deductions in sentential logic. This paper is a critical examination of Churchland's connectionist perspectives on philosophy of science. I argue that while sentential perspectives are not likely to be useful in understanding the reasoning of scientists, they do have an important place in philosophy of science.
Scientists present theories and arguments in sentential form.
Connectionism offers useful perspectives on philosophy of science by providing us alternative ways to construe how scientists interact with sentential representations. I illustrate how connectionist perspectives can assist us in understanding the activities of scientists by developing case studies from the history of modern cell biology. An HTML version of this paper is available. Hilary Putnam has argued that computational functionalism cannot serve as a foundation for the study of the mind, as every ordinary open physical system implements every finite-state automaton. I develop an account of implementation, linked to an appropriate class of automata, such that the requirement that a system implement a given automaton places a very strong constraint on the system.