Philosophy

Many artificial life researchers stress the interdisciplinary character of the field. Against such a backdrop, this report reviews and discusses artificial life, as it is depicted in, and as it interfaces with, adjacent disciplines (in particular, philosophy, biology, and linguistics), and in the light of a specific historical example of interdisciplinary research (namely cybernetics) with which artificial life shares many features. This report grew out of a workshop held at the Sixth European Conference on Artificial Life in Prague and features individual contributions from the workshop's eight speakers, plus a section designed to reflect the debates that took place during the workshop's discussion sessions. The major theme that emerged during these sessions was the identity and status of artificial life as a scientific endeavor.

Andy Clark has argued that language is ''in many ways the ultimate artefact'' (Clark, 1997, p. 218). Fuelling this conclusion is a view according to which the human brain is essentially no more than a pattern-completing device, while language is an external resource which is adaptively fitted to the human brain in such a way that it enables that brain to exceed its unaided (pattern-completing) cognitive capacities, in much the same way as a pair of scissors enables us to ''exploit our basic manipulative capacities to fulfil new ends'' (Clark, 1997, pp. 193-194). How should we respond to this bold reconceptualization of our linguistic abilities? First we need to understand it properly. So I begin by identifying and unpacking (and making a small ''Heideggerian'' amendment to) ClarkÕs main language-specific claims. That done I take a step back. ClarkÕs approach to language is generated from a theoretical perspective which sees cognition as distributed over brain, body, and world. So I continue my investigation of ClarkÕs incursion into linguistic territory by uncovering and illustrating those key ideas from the overall distributed cognition research programme which are particularly relevant in the present context. I then use this analysis as a springboard from which to examine a crucial issue that arises for ClarkÕs account of language, namely linguistic inner rehearsal. I argue that while there is much to recommend in ClarkÕs treatment of this issue, some significant difficulties remain to be overcome. Via this critique of ClarkÕs position, alongside some proposals for how the revealed problems might be addressed, I hope to edge us that bit closer to a full understanding of our linguistic abilities.

It is common these days to distinguish between three kinds of cognitive science or artificial intelligence: classical, connectionist, and (something like) embodied-embedded. Of course, all such attempts at neat-and-tidy categorization are undoubtedly guilty of over-simplification in one way or another. For example, researchers sometimes build models that combine aspects of more than one approach (e.g. when conventional connectionist networks are used as control systems for embodied agents). That noted, however, one method for separating out our three kinds of cognitive science, so as to understand more clearly their basic theoretical commitments, would be to identify, in a very general way, the sorts of machine that each takes to capture the fundamental character of intelligence. If we adopt this strategy, classicism will be defined by the manipulation of symbols using structure- sensitive processes, connectionism by unfolding patterns of activity in neurally inspired networks of si...

To my mind, being wrong is nowhere near as disheartening as being boring, so I am encouraged by the fact that, in the four chapters immediately preceding this one, four thinkers for whom I have nothing but the utmost intellectual respect have found my ongoing project to articulate the philosophical groundwork for a genuinely Heideggerian cognitive science interesting enough that they have taken the trouble to explain precisely why it is flawed. Just how deep the supposed flaws go depends on which set of criticisms one chooses to read. For Ratcliffe and Rehberg they go very deep indeed, since, for these thinkers, there is a sense in which the very idea of a Heideggerian cognitive science borders on the incoherent. Dreyfus and Rietveld, on the other hand, seem to agree with me that something worth calling a Heideggerian cognitive science is certainly possible; it's just that my version of it is seriously defective. Although being interesting and wrong is preferable to being boring and right, one aspires to be interesting and right. In what follows, then, I shall endeavour to resist what I take to be the most powerful (although admittedly not all) of the criticisms tabled in each of the chapters just mentioned. In setting up my contribution to the present volume in this way, I don't for one moment mean to suggest that criticizing my position is all, or indeed the most important thing, that these papers do. Far from it: the positive contributions they make in bringing the relations between Heideggerian philosophy and cognitive science into better viewthe multiply elusive 'and' in the identifier 'Heidegger and cognitive science', as Rehberg (this volume) would have itare a great deal more significant than their problematizations of my own view. Still, I am self-interested enough to spend my time here defending myself in the line of fire, which is why, in what follows, I shall be arguing that Ratcliffe, Rehberg, Dreyfus and Rietveld (in roughly that order) have further work to do before my letter of surrender arrives in their inboxes. That said, the goal of this chapter may also be expressed in a way that avoids the egocentric emphasis placed on it so far: that goal is to defend both the very idea of a Heideggerian cognitive science and a certain vision of what such a cognitive science will look like, at least in part. So, adopting something of a pantomime register, I shall suggest that the right response to Ratcliffe's (this volume) strident claim that there can be no cognitive science of Dasein (where 'Dasein' is Heidegger's term for the distinctive kind of entity that human beings as such are) is to shout back (with gusto) 'oh yes there can!'.

In 1637 the great philosopher, mathematician and natural scientist Rene Descartes published one of his most important texts, namely the Discourse on the Method of Rightly Conducting one's Reason and Seeking the Truth in the Sciences, commonly known simply as the Discourse (Cottingham et al. 1985a). 2 This event happened over 300 years before Turing, Ashby, Newell, Simon and the other giants of cybernetics and early artificial intelligence (AI) produced their seminal work. Approximately the same timespan separates the Discourse from the advent of the digital computer. Given these facts it will probably come as something of a surprise to at least some readers of this volume to discover that, in this text, Descartes reflects on the possibility of mechanizing mind. Not only that but, as I shall argue in this chapter, he elegantly identifies, and takes a far from anachronous or historically discredited stand on, a key question regarding the mechanization of mind, a question that, if we're honest with ourselves, we still don't really know how to answer. As I said, never underestimate Descartes.

Recent years have seen growing evidence of a fruitful engagement between phenomenology and cognitive science. This paper confronts an in-principle problem that stands in the way of this (perhaps unlikely) intellectual coalition, namely the fact that a tension exists between the transcendentalism that characterizes phenomenology and the naturalism that accompanies cognitive science. After articulating the general shape of this tension, I respond as follows. First, I argue that, if we view things through a kind of neo-McDowellian lens, we can open up a conceptual space in which phenomenology and cognitive science may exert productive constraints on each other. Second, I describe some examples of phenomenological cognitive science that illustrate such constraints in action. Third, I use the mutually constraining relationship at work here as the platform from which to bring to light a domesticated version of the transcendental and a minimal form of naturalism that are compatible with ea...

The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that: • a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.

Many artificial life researchers stress the interdisciplinary character of the field. Against such a backdrop, this report reviews and discusses artificial life, as it is depicted in, and as it interfaces with, adjacent disciplines (in particular, philosophy, biology, and linguistics), and in the light of a specific historical example of interdisciplinary research (namely cybernetics) with which artificial life shares many features. This report grew out of a workshop held at the Sixth European Conference on Artificial Life in Prague and features individual contributions from the workshop's eight speakers, plus a section designed to reflect the debates that took place during the workshop's discussion sessions. The major theme that emerged during these sessions was the identity and status of artificial life as a scientific endeavor. * The authors' names have been ordered as follows: The first-named was primarily responsible for coordinating and editing the present report. Next come the three other organizers of the workshop, in alphabetical order, followed by the four invited additional speakers, in alphabetical order. No other significance should be attached to the ordering.

Łukasz Afeltowicz, Nicolaus Copernicus University; Anna Borghi, University of Bologna & Institute of Cognitive Sciences and Technologies (CNR); Robert Clowes, New University of Lisbon; Victor Loughlin, University of Antwerp; Marek McGann, University of Limerick; Richard Menary, Macquarie University; Marcin Miłkowski, Institute of Philosophy and Sociology, Polish Academy of Sciences (Warsaw, project coordinator); Roger O’Shea, University of Limerick; Joanna Rączaszek-Leonardi, University of Warsaw; John Sutton, Macquarie University; Luca Tummolini, Institute of Cognitive Sciences and Technologies, Consiglio Nazionale delle Ricerche (CNR); Michael Wheeler, University of Stirling; Witold Wachowski, Centre for Philosophical Research (Warsaw).

Orthodox cognitive science claims that situated (world-embedded) activity can be explained as the outcome of in-the-head manipulations of representations by computational information processing mechanisms. But, in the eld of Arti cial Life, research into adaptive behaviour questions the primacy of the mainstream explanatory framework. This paper argues that such doubts are well-founded. Classical A.I. encountered fundamental problems in moving from toy worlds to dynamic unconstrained environments. I draw on work in behaviour-based robotics to suggest that such di culties are plausibly viewed as artefacts of the representational/computational architecture assumed in the classical paradigm. And merely moving into connectionism cannot save the received orthodoxy. If we adopt the perspective according to which neural networks are most naturally conceptualized as dynamical systems, it becomes appropriate to treat such networks as computational devices only if the network-dynamics are del...

The received opinion in mainstream cognitive science is that cognition is the manipulation of representations by computational information processing mechanisms. However, in this paper, I argue that cognition ought to be conceptualized not as computation, but as state-space evolution in certain classes of non-computational dynamical systems. Following a review of van Gelder's arguments for this dynamical cognition hypothesis, I suggest that the most compelling reasons for adopting a dynamical perspective come from research into situated (world-embedded) autonomous agents. We should think of cognitive architectures as control systems for the situated activity of su ciently complex embodied agents. I draw on key work in the simulation of adaptive behaviour which indicates that situatedness is best explained using the concept of dynamical coupling. I then present a preliminary sketch of other ways in which the conceptual framework of dynamics provides a powerful basis for thinking about and studying cognition.