Introduction

Computation and cognitive science

Nowadays, it has become almost a matter of course to say that the human mind is like a computer. Folks in all walks of life talk of ‘programming’ themselves, ‘multi-tasking’, running different ‘operating systems’, and sometimes of ‘crashing’ and being ‘rebooted’. Few who have used computers have not been touched by the appeal of the idea that our inner workings somehow resemble computing machines. The success of modern day computational psychology appears to bears witness to the explanatory and predictive pay-off in positing a connection between computers and minds. Among its other virtues, the computational framework has rendered theorising about inner processes respectable, it has provided a unified and naturalistic arena in which to conduct debates about psychological models, and it provides the tantalising possibility of accurately simulating and reproducing psychological processes.

There is almost universal agreement that the mind is in some sense like a computer. But consensus quickly ends once we ask how. Even after more than thirty years of model building, and a wealth of empirical work, surprisingly little consensus exists on the correct answer to this question. What is more, disagreement tends to lie at a relatively fundamental level. There is little agreement about the content of the notion of computation, what it means for a physical system, like the brain, to implement a computation, the broad-brush computational architecture of the mind, or how computational models fit with other models of the mind, such as control theoretic models, statistical models, or dynamical systems theory.

This special issue targets these questions. The contributors analyse the role that computation plays in cognitive science, and the implications, based on our current evidence, this has for the architecture of human psychology. The intention is not only to secure firmer ground for contemporary cognitive science, but also to envision cognitive science’s next steps.

Let us take up the questions above. First, what exactly do we mean by computation, and how does the notion of computation differ from related notions, such as information processing? Is there a single notion of computation, or should we be pluralists about computation? Second, what does it mean to say that a physical system, like the human brain, implements a computation? How is representational content involved in implementation, if at all? What are the necessary conditions for implementation to obtain? Under what conditions do two systems, for example an electronic PC and a human brain, implement the same computation? Third, granted that one can agree about implementation, what evidence can one bring to bear to determine the computational architecture of the human mind? How do we assess the merits of a computational model, and which computational architectures can we already, based on our current evidence, rule in or out? Fourth, how do other approaches to explaining cognition, such as statistical theory, control theory, and coupled-oscillator models, relate to computational models of the mind? Are they rivals to explaining the mind in terms of computation, or themselves types of computation?

The papers in this special issue fall into four groups, corresponding to the four groups of questions above:

• 1.

  Distinguishing computation from related notions (e.g. information processing)

• 2.

  Theories of implementation of computation

• 3.

  Computation at work in cognitive science

• 4.

  Projected successors to the notion of computation in cognitive science