Information Processing, Computation and Cognition

Computation and information processing are among the most fundamental notions in cognitive science. They are also among the most imprecisely discussed. Many cognitive scientists take it for granted that cognition involves computation, information processing, or both – although others disagree vehemently. Yet different cognitive scientists use ‘computation’ and ‘information processing’ to mean different things, sometimes without realizing that they do. In addition, computation and information processing are surrounded by several myths; first and foremost, that they are the same thing. In this paper, we address this unsatisfactory state of affairs by presenting a general and theory-neutral account of computation and information processing. We also apply our framework by analyzing the relations between computation and information processing on one hand and classicism and connectionism/computational neuroscience on the other. We defend the relevance to cognitive science of both computation, at least in a generic sense, and information processing, in three important senses of the term. Our account advances several foundational debates in cognitive science by untangling some of their conceptual knots in a theory-neutral way. By leveling the playing field, we pave the way for the future resolution of the debates’ empirical aspects

Filling the Gaps: Hume and Connectionism on the Continued Existence of Unperceived Objects

In Book I, part iv, section 2 of the Treatise, "Of scepticism with regard to the senses," Hume presents two different answers to the question of how we come to believe in the continued existence of unperceived objects. He rejects his first answer shortly after its formulation, and the remainder of the section articulates an alternative account of the development of the belief. The account that Hume adopts, however, is susceptible to a number of insurmountable objections, which motivates a reassessment of his original proposal. This paper defends a version of Hume's initial explanation of the belief in continued existence and examines some of its philosophical implications

A Connectionist Theory of Phenomenal Experience

When cognitive scientists apply computational theory to the problem of phenomenal consciousness, as many of them have been doing recently, there are two fundamentally distinct approaches available. Either consciousness is to be explained in terms of the nature of the representational vehicles the brain deploys; or it is to be explained in terms of the computational processes defined over these vehicles. We call versions of these two approaches vehicle and process theories of consciousness, respectively. However, while there may be space for vehicle theories of consciousness in cognitive science, they are relatively rare. This is because of the influence exerted, on the one hand, by a large body of research which purports to show that the explicit representation of information in the brain and conscious experience are dissociable, and on the other, by the classical computational theory of mind – the theory that takes human cognition to be a species of symbol manipulation. But two recent developments in cognitive science combine to suggest that a reappraisal of this situation is in order. First, a number of theorists have recently been highly critical of the experimental methodologies employed in the dissociation studies – so critical, in fact, it’s no longer reasonable to assume that the dissociability of conscious experience and explicit representation has been adequately demonstrated. Second, classicism, as a theory of human cognition, is no longer as dominant in cognitive science as it once was. It now has a lively competitor in the form of connectionism; and connectionism, unlike classicism, does have the computational resources to support a robust vehicle theory of consciousness. In this paper we develop and defend this connectionist vehicle theory of consciousness. It takes the form of the following simple empirical hypothesis: phenomenal experience consists in the explicit representation of information in neurally realized PDP networks. This hypothesis leads us to re-assess some common wisdom about consciousness, but, we will argue, in fruitful and ultimately plausible ways

Neurons and symbols: a manifesto

We discuss the purpose of neural-symbolic integration including its principles, mechanisms and applications. We outline a cognitive computational model for neural-symbolic integration, position the model in the broader context of multi-agent systems, machine learning and automated reasoning, and list some of the challenges for the area of neural-symbolic computation to achieve the promise of effective integration of robust learning and expressive reasoning under uncertainty

Is Science eliminating Ordinary Talk?

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Fewer epistemological challenges for connectionism

Seventeen years ago, John McCarthy wrote the note Epistemological challenges for connectionism as a response to Paul Smolensky’s paper 'On the proper treatment of connectionism'. I will discuss the extent to which the four key challenges put forward by McCarthy have been solved, and what are the new challenges ahead. I argue that there are fewer epistemological challenges for connectionism, but progress has been slow. Nevertheless, there is now strong indication that neural-symbolic integration can provide effective systems of expressive reasoning and robust learning due to the recent developments in the field

The Resilience of Computationalism

Computationalism—the view that cognition is computation—has always been controversial. It faces two types of objection. According to insufficiency objections, computation is insufficient for some cognitive phenomenon X. According to objections from neural realization, cognitive processes are realized by neural processes, but neural processes have feature Y and having Y is incompatible with being (or realizing) computations. In this paper, I explain why computationalism has survived these objections. Insufficiency objections are at best partial: for all they establish, computation may be sufficient for cognitive phenomena other than X, may be part of the explanation for X, or both. Objections from neural realization are based either on a false contrast between feature Y and computation or on an account of computation that is too vague to yield the desired conclusion. To adjudicate the dispute between computationalism and its foes, I will conclude that we need a better account of computation

Psychological Innateness and Representations of God: Implications of the Innateness Controversy for the Study Of Religious Concepts

The author examines a means by which cognitive psychological notions of innateness might address the question ofhow the concept ofGod might be said to he \"natural\" or \"instinctive.\" He draws a distinction hetM\'een innate cognitive nuchanisms and innate cognitive content, and examines the concept of innateness from the perspectives of two major cognitive psychological theories of mind: computationalism and connectionism. He argues that, from the cognitive psychological perspective, concept(s) of God (or gods) cannot be said to be strictly innate, but that the development of the God concept does appear to be constrained by innate psychological structures and processes. He concludes by suggesting that the psychological origin of the God-concept may be best described as a sort of \"primal behavior\"—the inevitable product of interaction between innately determined psychological mechanisms and aspects of the environment that are common to all members of a population

Hume's Legacy: A Cognitive Science Perspective

Hume is an experimental philosopher who attempts to understand why we think, feel, and act as we do. But how should we evaluate the adequacy of his proposals? This chapter examines Hume’s account from the perspective of interdisciplinary work in cognitive science