I propose a new approach to the constitutive problem of psychology ‘what is mind?’ The first section introduces modifications of the received scope, methodology, and evaluation criteria of unified theories of cognition in accordance with the requirements of evolutionary compatibility and of a mature science. The second section outlines the proposed theory. Its first part provides empirically verifiable conditions delineating the class of meaningful neural formations and modifies accordingly the traditional conceptions of meaning, concept and thinking. This analysis is part (...) of a theory of communication in terms of inter-level systems of primitives that proposes the communication-understanding principle as a psychological invariance. It unifies a substantial amount of research by systematizing the notions of meaning, thinking, concept, belief, communication, and understanding and leads to a minimum vocabulary for this core system of mental phenomena. Its second part argues that written human language is the key characteristic of the artificially natural human mind. Overall, the theory both supports Darwin’s continuity hypothesis and proposes that the mental gap is within our own species. (shrink)

I critically examine some provocative arguments that John Searle presents in his book The Rediscovery of Mind to support the claim that the syntactic states of a classical computational system are "observer relative" or "mind dependent" or otherwise less than fully and objectively real. I begin by explaining how this claim differs from Searle's earlier and more well-known claim that the physical states of a machine, including the syntactic states, are insufficient to determine its semantics. In contrast, his more recent (...) claim concerns the syntax, in particular, whether a machine actually has symbols to underlie its semantics. I then present and respond to a number of arguments that Searle offers to support this claim, including whether machine symbols are observer relative because the assignment of syntax is arbitrary, or linked to universal realizability, or linked to the sub-personal interpretive acts of a homunculus, or linked to a person's consciousness. I conclude that a realist about the computational model need not be troubled by such arguments. Their key premises need further support. (shrink)

I focus on and criticize John Searle's argument against a classical computational view of the mind according to which the attribution of syntax is observer relative (in Searle, Rediscovery of Mind, MIT Press, 1992). Searle's argument is interesting inasmuch as it differs from his previous and more well-known argument that syntax is not sufficient for semantics. This argument aims to undercut even the syntax as something that exists only in the eye of the beholder. I show that Searle's argument rests (...) on premises that go unsupported. (shrink)

Can the output of human cognition be predicted from the assumption that it is an optimal response to the information-processing demands of the environment? A methodology called rational analysis is described for deriving predictions about cognitive phenomena using optimization assumptions. The predictions flow from the statistical structure of the environment and not the assumed structure of the mind. Bayesian inference is used, assuming that people start with a weak prior model of the world which they integrate with experience to develop (...) stronger models of specific aspects of the world. Cognitive performance maximizes the difference between the expected gain and cost of mental effort. Memory performance can be predicted on the assumption that retrieval seeks a maximal trade-off between the probability of finding the relevant memories and the effort required to do so; in categorization performance there is a similar trade-off between accuracy in predicting object features and the cost of hypothesis formation; in casual inference the trade-off is between accuracy in predicting future events and the cost of hypothesis formation; and in problem solving it is between the probability of achieving goals and the cost of both external and mental problem-solving search. The implemention of these rational prescriptions in neurally plausible architecture is also discussed. (shrink)

In their critique of connectionist models Fodor and Pylyshyn (1988) dismiss such models as not being cognitive or psychological. Evaluating Fodor and Pylyshyn's critique requires examining what is required in characterizating models as 'cognitive'. The present discussion examines the various senses of this term. It argues the answer to the title question seems to vary with these different senses. Indeed, by one sense of the term, neither representa-tionalism nor connectionism is cognitive. General ramifications of such an appraisal are discussed and (...) alternative avenues for cognitive research are suggested. (shrink)

Abstract In the first part of this essay (Russell, 1988a) I argued that ?cognisance? (roughly: a subject's knowledge of his relation to the physical world as an experiencer of it) cannot be explained in terms of a syntactic theory of mind, due to the ?referential? and ?holistic? nature of this knowledge. The syntactic account of the higher mental functions is immediately intelligible to us due to its derivation from computer technology, so this would not appear to be a happy result (...) for scientific psychology. In this paper I outline a strategy for developing a scientific psychology of cognisance, beginning from the assumption that such a theory should have a similar status to Chomsky's competence theory of human grammar, whilst diverging from Chomsky on the question of how such a theory should be answerable to data. Most of the paper is taken up with illustrating the way in which Jean Piaget's theory of mental development in humans is at least a first approximation to such a theory. (shrink)

I distinguish between being cognisant and being able to perform intelligent operations. The former, but not the latter, minimally involves the capacity to make adequate judgements about one's relation to objects in the environment. The referential nature of cognisance entails that the mental states of cognisant systems must be inter-related holistically, such that an individual thought becomes possible because of its relation to a system of potential thoughts. I use Gareth Evans' 'Generality Constraint' as a means of describing how the (...) reference and holism of mental states in cognisant systems are mutually dependent. Next, I describe attempts to deny the relevance of holism and reference by positing a mentalese. These attempts fail because the meanings of symbols are under determined, with there being no principled means of distinguishing between the mental tokening of a symbol and its disambiguation. I argue that the connectionist meta-theory does not encounter this problem because it is able to encompass the holism of the mental. Recent attempts to show that symbol processing theories of thought must be preferred to connectionist theories do not work. Despite appearances to the contrary, the Generality Constraint favours connectionist not symbol-processing theories. (shrink)

Small batch manufacture dominates the manufacturing sector of a growing number of industrialised countries. The organisational structures and management methods currently adopted in such enterprises are firmly based upon historical developments which started with individual craftsmen. These structures and methods are primarily concerned with the co-ordination of human activities, rather than with the management of theknowledge process underlying the creation of products.This paper argues that it is the failure to understand this knowledge process and its effective integration at aKnowledge Level (...) which presents the real barrier to increased flexibility, not, as is presently perceived, a lack of suitableInformation Level integration. Potential techniques and methodologies for achievingKnowledge Level integration are beginning to emerge from Artificial Intelligence research. Realisation of full Knowledge Level integration will not only require further research into the AI techniques and methodologies involved, but also an understanding of the wider human aspects of their application. Some questions concerning the effective coupling of human and artificial intelligence to achieve Knowledge Level integration of the product creation process are presented. (shrink)