Levellism and the Method of Abstraction

ion can be seen as doing for discrete systems what differential calculus has traditionally done for analogue systems. Likewise, the use of predicates is essential in subjects like information and computer science, where discrete observables are paramount and hence predicates are required to describe a system behaviour. In particular, state-based methods like Z (Hayes and Flinn [1993], Spivey [1992]) provide notation for structuring complex observables and behaviours in terms of simpler ones. Their primary concern is with the syntax for expressing those predicates, an issue we shall try to avoid in this paper by stating predicates informally. The time has come now to combine approximating, moderated LoAs to form the primary concept of the method of abstraction. 2.6. Gradient of abstraction For a given (empirical or conceptual) system or feature, different LoAs correspond to different representations or views. A Gradient of Abstractions (GoA) is a formalism defined to facilitate discussion of discrete systems over a range of LoAs. Whilst a LoA formalises the scope or granularity of a single model, a GoA provides a way of varying the LoA in order to make observations at differing levels of abstraction. For example, in evaluating wine we might be interested in the GoA consisting of the “tasting” and “purchasing” LoAs, whilst in managing a cellar we might be interested in the GoA consisting of the “cellaring” LoA together with a sequence of annual results of observation using the “tasting” LoA. L. Floridi – J. W. Sanders, Levellism and the Method of Abstraction ——————————————————————————————————————————————-—————— ——————— Information Ethics Group – Research Report 22.11.04 ———— 13 In general, the observations at each LoA must be explicitly related to those at the others; to do so, we use a family of relations between the LoAs. For this, we need to recall some (standard) preliminary notation. Notation. A relation R from a set A to a set C is a subset of the Cartesian product A × C. R is thought of as relating just those pairs (a, c) that belong to the relation. The reverse of R is its mirror image: {(c, a) | (a, c) ∈ R}. A relation R from A to C translates any predicate p on A to the predicate PR(p) on C that holds at just those c:C, which are the image through R of some a:A satisfying p PR(p)(c) = ∃a: A R(a,c) ∧ p(a). We have finally come to the main definition of the paper. Definition. A gradient of abstractions, GoA, is defined to consist of a finite set {Li | 0 ≤ i < n} of moderated LoAs Li and a family of relations Ri,j ⊆ Li × Lj, for 0 ≤ i ≠ j < n, relating the observables of each pair Li and Lj of distinct LoAs in such a way that: 1. the relationships are inverse: for i ≠ j, Ri,j is the reverse of Rj,i 2. the behaviour pj at Lj is at least as strong as the translated behaviour PRi,j(pi)

[1]  Herbert A. Simon,et al.  The Sciences of the Artificial , 1970 .

[2]  S. Salthe Evolving Hierarchical Systems: Their Structure and Representation , 1985 .

[3]  W. Wimsatt Reductionism, Levels of Organization, and the Mind-Body Problem , 1976 .

[4]  Luciano Floridi,et al.  ON THE LOGICAL UNSOLVABILITY OF THE GETTIER PROBLEM , 2004, Synthese.

[5]  William J. Rapaport The Turing Test: Verbal Behavior as the Hallmark of Intelligence edited by Stuart Shieber , 2005, Comput. Linguistics.

[6]  Z. Pylyshyn,et al.  Computation and Cognition: Toward a Foundation for Cognitive Science.Epistemology and Cognition , 1988 .

[7]  J. Heijenoort From Frege to Gödel: A Source Book in Mathematical Logic, 1879-1931 , 1967 .

[8]  Richard Reviewer-Granger Unified Theories of Cognition , 1991, Journal of Cognitive Neuroscience.

[9]  J. Bell,et al.  The Theory of Local Beables , 1975 .

[10]  J. Michael Spivey,et al.  The Z notation - a reference manual , 1992, Prentice Hall International Series in Computer Science.

[11]  Luciano Floridi,et al.  Consciousness, Agents and the Knowledge Game , 2005, Minds and Machines.

[12]  Madhav Erraguntla,et al.  Simulation modeling at multiple levels of abstraction , 1998, 1998 Winter Simulation Conference. Proceedings (Cat. No.98CH36274).

[13]  Roberto Poli,et al.  The Basic Problem of the Theory of Levels of Reality , 2001 .

[14]  J. Barwise,et al.  The Liar: An Essay on Truth and Circularity , 1987 .

[15]  A. M. Turing,et al.  Computing Machinery and Intelligence , 1950, The Philosophy of Artificial Intelligence.

[16]  Rónán O'Beirne,et al.  The Blackwell Guide to the Philosophy of Computing and Information , 2004 .

[17]  Jonathan Schaffer,et al.  Is There a Fundamental Level , 2003 .

[18]  C. I. Lewis,et al.  The Semantic Conception of Truth and the Foundations of Semantics , 1944 .

[19]  Ian J. Hayes,et al.  Specification case studies , 1987 .

[20]  Luciano Floridi,et al.  On the intrinsic value of information objects and the infosphere , 2002, Ethics and Information Technology.

[21]  S. Shieber,et al.  Book Review: The Turing Test: Verbal Behavior as the Hallmark of Intelligence, edited by Stuart Shieber , 1986, CL.

[22]  C. L. Foster Algorithms, abstraction and implementation : levels of detail in cognitive science , 1992 .

[23]  Donald Davidson,et al.  On the Very Idea of a Conceptual Scheme , 1973 .

[24]  C. Emmeche,et al.  EXPLAINING EMERGENCE: TOWARDS AN ONTOLOGY OF LEVELS , 1997 .

[25]  Woodrow Barfield,et al.  The Philosophy of Presence : From Epistemic Failure to Successful Observability , 2004 .

[26]  G. Mann The Quark and the Jaguar: adventures in the simple and the complex , 1994 .

[27]  Allen Newell,et al.  Reflections on the Knowledge Level , 1993, Artif. Intell..

[28]  Ron McClamrock,et al.  Marr's three levels: A re-evaluation , 1991, Minds and Machines.

[29]  Gavan Lintern,et al.  Dynamic patterns: The self-organization of brain and behavior , 1997, Complex.

[30]  Kai Engelhardt,et al.  Data Refinement: Model-Oriented Proof Methods and their Comparison , 1998 .

[31]  R. Weale Vision. A Computational Investigation Into the Human Representation and Processing of Visual Information. David Marr , 1983 .

[32]  David Marr,et al.  VISION A Computational Investigation into the Human Representation and Processing of Visual Information , 2009 .

[33]  S. Brison The Intentional Stance , 1989 .

[34]  Allen Newell,et al.  The Knowledge Level , 1989, Artif. Intell..

[35]  Luciano Floridi,et al.  On the Morality of Artificial Agents , 2004, Minds and Machines.

[36]  Helen E. Longino,et al.  Discovering Complexity: Decomposition and Localization as Strategies in Scientific Research , 1995 .

[37]  H. Hendriks-jansen,et al.  In Praise of Interactive Emergence: Or Why Explanations Don''t Have to Wait for Implementations , 1989 .

[38]  L. Floridi OPEN PROBLEMS IN THE PHILOSOPHY OF INFORMATION , 2004 .

[39]  Jancis Robinson,et al.  Vintage timecharts: The pedigree and performance of fine wines to the year 2000 , 1989 .

[40]  David Thomas,et al.  The Art in Computer Programming , 2001 .

[41]  Tom M. Mitchell,et al.  Machine learning, International Edition , 1997, McGraw-Hill Series in Computer Science.

[42]  Harold Chapman Brown Structural Levels in the Scientist's World , 1916 .

[43]  Nenad Medvidovic,et al.  A Formal Approach to Heterogeneous Software Modeling , 2000, FASE.

[44]  C. H. Dagli,et al.  Emergence and artificial life , 2003, IEMC '03 Proceedings. Managing Technologically Driven Organizations: The Human Side of Innovation and Change.

[45]  Patrick Hughes,et al.  Vicious Circles and Infinity: A Panoply of Paradoxes , 1975 .

[46]  Walter Mosley Six Easy Pieces , 2003 .

[47]  Zenon W. Pylyshyn,et al.  Computation and Cognition: Toward a Foundation for Cognitive Science , 1984 .

[48]  H. Simon,et al.  The sciences of the artificial (3rd ed.) , 1996 .

[49]  H. Putnam,et al.  Unity of Science as a Working Hypothesis , 1958 .

[50]  T. Nagel Mortal Questions: What is it like to be a bat? , 2012 .