Physical Computation and Cognitive Science PDF
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Studies in Applied Philosophy, Epistemology and Rational Ethics Nir Fresco Physical Computation and Cognitive Science Studies in Applied Philosophy, Epistemology and Rational Ethics Volume 12 Editor-in-Chief LorenzoMagnani,UniversityofPavia,Italy [email protected] AboutThisSeries StudiesinAppliedPhilosophy,EpistemologyandRationalEthics(SAPERE)publishesnew developmentsandadvancesinallthefieldsofphilosophy,epistemology,andethics,bringing themtogetherwithaclusterofscientificdisciplinesandtechnologicaloutcomes:fromcom- putersciencetolifesciences,fromeconomics,law,andeducationtoengineering,logic,and mathematics,frommedicinetophysics,humansciences,andpolitics.Itaimsatcoveringall thechallengingphilosophicalandethicalthemesofcontemporarysociety,makingthemap- propriatelyapplicabletocontemporarytheoretical,methodological,andpracticalproblems, impasses, controversies, and conflicts. The series includes monographs, lecture notes, se- lected contributions from specialized conferences and workshops as well as selected PhD theses. EditorialBoard AtochaAliseda UniversidadNacionalAutónomadeMéxico(UNAM),Coyoacan,Mexico GiuseppeLongo CentreCavaillès,CNRS-EcoleNormaleSupérieure,Paris,France ChrisSinha LundUniversity,Lund,Sweden PaulThagard WaterlooUniversity,Ontario,Canada JohnWoods UniversityofBritishColumbia,Vancouver,BCCanada Forfurthervolumes: http://www.springer.com/series/10087 Nir Fresco Physical Computation and Cognitive Science ABC NirFresco SchoolofHumanities&Languages, UniversityofNewSouthWales Sydney Australia ISSN2192-6255 ISSN2192-6263 (electronic) ISBN978-3-642-41374-2 ISBN978-3-642-41375-9 (eBook) DOI10.1007/978-3-642-41375-9 SpringerHeidelbergNewYorkDordrechtLondon LibraryofCongressControlNumber:2013949443 (cid:2)c Springer-VerlagBerlinHeidelberg2014 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpartof thematerialisconcerned,specificallytherightsoftranslation,reprinting,reuseofillustrations,recitation, broadcasting,reproductiononmicrofilmsorinanyotherphysicalway,andtransmissionorinformation storageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilarmethodology nowknownorhereafterdeveloped.Exemptedfromthislegalreservationarebriefexcerptsinconnection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. 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Printedonacid-freepaper SpringerispartofSpringerScience+BusinessMedia(www.springer.com) To my beloved wife, Calanit, and my lovely daughters, Leah & Noa Foreword Nir Fresco tackles the nontrivial question of “What is computation?”. His thorough review includes explication and critique of accounts of computation ranging from Turing's, as is embodied by the Turing machine, to more recent accounts from the computational theory of mind. He offers his own account of concrete digital computation that is based on a critical analysis of the role information plays in computation and how differing notions of information fare in the context of computation. His two-pronged approach will appeal to philosophically inclined computer scientists who want to understand better common theoretical claims in cognitive science. This book provides a thorough and timely analysis of differing accounts of computation while advancing the important role that information plays in understanding computation. --Marty J. Wolf, Professor of Computer Science, Bemidji State University Preface It is my great pleasure to write this preface for Dr. Nir Fresco’s book “Physical Computation and Cognitive Science” based on his doctoral thesis “Concrete Digital Computation: Competing Accounts and its Role in Cognitive Science” of which I was the supervisor. Nir was enrolled in Philosophy at UNSW as a part-time PhD student while working full-time as a computing professional, a very reflective one. Not only did he submit his thesis early he also found time to publish six papers related to it on the way through. A truly remarkable achievement. Nir’s main project in this book is to clarify the nature of computation, but he has a special interest in its explanatory role in cognitive science and understanding cognition. Computation is an ambiguous concept and computer scientists, philosophers and cognitive scientists who use the concept can contest some claim using it and not realise they are not actually in disagreement with each other, even though it looks as though they are. This cuts both ways: sometimes they talk past each other and think they are in agreement when they are not. A practical aim of this book is to help with this problem by clarifying the nature of computation. In very brief compass but sufficient to point to the substantial scope of this volume, here is a selective description of its eight chapters. The first sets the stage and discusses computation in cognitive science and a distinction between three kinds of representation in computation: intrinsic, mathematical and extrinsic. The central question to be answered is what does it take for a system to perform physical digital computation and some important distinctions start the discussion here. Chapters 2 through to 7 form the heart of the book’s answer to this question. Chapter 2, propaedeutic in nature, discusses adequacy criteria for evaluating accounts of computation. The criteria proposed by five influential theorists are considered: Brian Cantwell Smith, Gualtiero Piccinini, John von Neumann, David Chalmers and Matthias Scheutz. Three of Smith’s criteria are discussed, six of Piccinini’s and three of von Neumann’s as well as the single criterion proposed by Chalmers and Scheutz. There is some overlap among these and Nir argues cogently for six criteria broadly in agreement with Piccinini. These six criteria concern what an adequate account should explain and classify. They are, using Nir’s terminology, the following: the conceptual, implementation, dichotomy, miscomputation, taxonomy and program execution criteria. The first requires being able to explain basic concepts in computation such as that of a computer program, algorithm and computer architecture. The X Preface second concerns the implementation by physical systems of abstract computation. The third requires the accurate classification of paradigmatic computing systems distinguishing them from non-computing systems. The fourth and fifth require accounting for miscomputation and appropriately classifying computational systems of differing powers, respectively. The sixth requires an account to explain the relation between program execution and concrete digital computation. Adequacy criteria having been chosen, we are in a position to see how well competing accounts of computation measure up. Chapter 3, as Nir says in its title, starts at the beginning and examines Alan Turing’s account. Unsurprisingly at this stage, but informatively his account does not do well. Turing was answering a related but different question. Chapter 4 may be seen as a kind of interlude in the proceedings, not really discussing a serious account of computation. Titled, ‘The Triviality “Account” Examined’, it discusses attempts by two philosophers John Searle and Hilary Putnam to undermine the computational view of cognition by arguing in effect that every physical object (of sufficient everyday complexity) computes, trivialising the notion of what it is to compute. The exercise of arguing against this view is instructive. The next three chapters deal successively with semantic accounts of computation in Chapter 5, information processing accounts in Chapter 6 and more heterogeneously causal and functional accounts in Chapter 7. None of the three semantic accounts in Chapter 5 passes muster as accounts of concrete computation. On these accounts of computation, representation is the central notion and, more specifically, extrinsic (roughly, external world) representation. These semantic accounts are the physical symbol system account (PSS), the formal symbol manipulation account (FSM) and a reconstruction of B.C. Smith’s participatory account. FSM has been the most influential of these accounts especially in cognitive science and the critique here should contribute to a useful rethink. Two accounts do better, one each from chapters 6 and 7. In Chapter 6 the Instructional Information Processing account (IIP) does well as does the Mechanistic account in Chapter 7. Neither of these appeals to extrinsic representation for the explanation of computation. Chapter 6 on computation as information processing explores what this common view could mean. Nir distinguishes four kinds of information: two non- semantic kinds (Shannon and algorithmic) and two semantic kinds (declarative and instructional). He argues that only an instructional information processing account, a view he introduces and develops here, can satisfy the adequacy criteria. Chapter 7 focuses on three fairly recent non-semantic accounts of concrete digital computation. The first two of these are primarily causal and the last causal and functional. The first, called the Gandy-Sieg account, synthesises the older views of Robin Gandy and the more recent work of Wilfried Sieg. Concentrating on machine computation this view requires the system’s operation to be describable as a sequence of state transitions and has an emphasis on physical requirements for computation and, hence, (on some interpretations) implementation. Preface XI The second of these accounts is the algorithm execution account. As the name suggests this view ties computation to acting in accordance with an algorithm. There is an older view of Robert Cummins that is significantly refined by Jack Copeland so as not to succumb to trivialisation (as in Chapter 3). To this end Copeland puts constraints on implementation, requiring a specification of the basic architecture of the system and an algorithm specific to the primitive operations of the architecture as well as the possibility of a labelling of the system’s parts subject to special conditions. The third view is Piccinini’s mechanistic account. This non-semantic not exclusively causal view focuses on the functional/organisational features of the physical computing system. A central notion is that of a ‘digit’, a stable discrete state of a component of the system whose type can be reliably distinguished by it. Concatenations of digits are called ‘strings’ and can be either data or rules depending on their functional role in the system. On this view, a digital computing system is a mechanism with the function of mapping input strings (paired perhaps with internal states) into output strings according to general rules. This quick review of these important accounts omits the instructive discussions of the way they fail or pass the six criteria of adequacy. The subtlety of thought on show in the first seven chapters bears further fruit in the last when applied, among other things, to the role of computation in cognitive science. Chapter 8 is titled ‘Computation Revisited in the Context of Cognitive Science’ and covers a lot of ground. Two early positions defended in the first two sections are firstly that nontrivial computations typically only process implicit intrinsic and mathematical representations, not extrinsic ones and secondly that computational explanations of cognition will be unintelligible unless there is commitment to a single interpretation of the key phrase ‘digital computation’. The largest third section on the explanatory role of computation in cognitive science discusses the explanatory frameworks of computationalism, connectionism and dynamicism arguing that they are not mutually exclusive and opening the way for their integration. This section also discusses computational neuroscience, neural computation and the nature of mechanistic and non-mechanistic explanations. The chapter closes with some general remarks on computation and cognition. A final remark about this book and its provenance and author. In the second half of 2013 Nir was awarded the international Goldberg Memorial Prize. This prize, awarded by the International Association for Computing and Philosophy, is for outstanding graduate research. As noted above, Nir already had 6 publications written during his PhD candidacy. Ideas from all of these contributed to his doctorate and provided some of the rationale for this prestigious award. They will find a wider audience here. Dr. Phillip Staines Philosophy Discipline School of Humanities and Languages University of New South Wales Abstract There are currently considerable confusion and disarray about just how we should view computationalism, connectionism and dynamicism as explanatory frameworks in cognitive science. A key source of this ongoing conflict among the central paradigms in cognitive science is an equivocation on the notion of computation simpliciter. ‘Computation’ is construed differently by computationalism, connectionism, dynamicism and computational neuroscience. I claim that these central paradigms, properly understood, can contribute to an integrative cognitive science. Yet, before this claim can be defended, a better understanding of ‘computation’ is required. ‘Digital computation’ is an ambiguous concept. It is not just the classical dichotomy between analogue and digital computation that is the basis for the equivocation on ‘computation’ simpliciter in cognitive science, but also the diversity of extant accounts of digital computation. What does it take for a physical system to perform digital computation? There are many answers to this question ranging from Turing machine computation, through the formal manipulation of symbols, the execution of algorithms and others, to strong pancomputationalism, according to which every physical system computes every Turing-computable function. Despite some overlap among them, extant accounts of concrete digital computation are intensionally and extensionally non- equivalent, thereby rendering ‘digital computation’ ambiguous. The objective of this book is twofold. First, it is to promote a clearer understanding of concrete digital computation. Accordingly, the main underlying thesis of the book is that not only are extant accounts of concrete digital computation non-equivalent, but most of them are inadequate. In the course of examining several key accounts of concrete digital computation, I also propose the instructional information processing account, according to which nontrivial digital computation is the processing of discrete data in accordance with finite instructional information. The second objective is to establish the foundational role of computation in cognitive science whilst rejecting the extrinsically representational nature of computation proper. Keywords: Cognitive Science, Computability, Computationalism, Concrete Computation, Connectionism, Data, Digital Computation, Information, Turing Machine.
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