Towards a General Model of Applying Science

How is scientific knowledge used, adapted, and extended in deriving phenomena and real‐world systems? This paper aims at developing a general account of ‘applying science’ within the exemplar‐based framework of Data‐Oriented Processing (DOP), which is also known as Exemplar‐Based Explanation (EBE). According to the exemplar‐based paradigm, phenomena are explained not by deriving them all the way down from theoretical laws and boundary conditions but by modelling them on previously derived phenomena that function as exemplars. To accomplish this, DOP proposes to maintain a corpus of derivation trees of previous phenomena together with a matching algorithm that combines subtrees from the corpus to derive new phenomena. By using a notion of derivational similarity, a new phenomenon can be modelled as closely as possible on previously explained phenomena. I will propose an instantiation of DOP which integrates theoretical and phenomenological modelling and which generalises over various disciplines, from fluid mechanics to language technology. I argue that DOP provides a solution for what I call Kuhn’s problem and that it redresses Kitcher’s account of explanation.

[1]  Khalil Sima'an,et al.  A memory-based model of syntactic analysis: data-oriented parsing , 1999, J. Exp. Theor. Artif. Intell..

[2]  M. V. Dyke.  Entry flow in a channel , 1970, Journal of Fluid Mechanics.

[3]  P. Kitcher.  Explanatory unification and the causal structure of the world , 1989 .

[4]  T. Kuhn.  The Structure of Scientific Revolutions 2nd edition , 1970 .

[5]  Kurt VanLehn,et al.  Analogy Events: How Examples are Used During Problem Solving , 1998, Cogn. Sci..

[6]  Susan G. Sterrett,et al.  Models of Machines and Models of Phenomena , 2006 .

[7]  C. Hempel,et al.  Studies in the Logic of Explanation , 1948, Philosophy of Science.

[8]  Marcel Boumans,et al.  Built-In Justification , 1999 .

[9]  Tobias Nipkow,et al.  Term rewriting and all that , 1998 .

[10]  C. Habel,et al.  Language , 1931, NeuroImage.

[11]  Hinrich Schütze,et al.  Book Reviews: Foundations of Statistical Natural Language Processing , 1999, CL.

[12]  H. Kyburg,et al.  How the laws of physics lie , 1984 .

[13]  Thomas Nickles,et al.  Thomas Kuhn: Normal Science: From Logic to Case-Based and Model-Based Reasoning , 2002 .

[14]  T. Kuhn,et al.  The Structure of Scientific Revolutions. , 1964 .

[15]  Rens Bod.  Exemplar-Based Explanation , 2005 .

[16]  Brian Falkenhainer,et al.  The Structure-Mapping Engine: Algorithm and Examples , 1989, Artif. Intell..

[17]  P. Tichý.  Constructions , 1986, Philosophy of Science.

[18]  Ivan A. Sag,et al.  Syntactic Theory: A Formal Introduction , 1999, Computational Linguistics.

[19]  Rens Bod,et al.  Memory-Based Models of Melodic Analysis: Challenging the Gestalt Principles , 2002 .

[20]  Eugene Charniak,et al.  Statistical Techniques for Natural Language Parsing , 1997, AI Mag..

[21]  David Speiser.  Die Werke von Daniel Bernoulli , 1987 .

[22]  Margaret Morrison,et al.  Models as Mediators , 1999 .

[23]  Stephan Hartmann,et al.  Models and Stories in Hadron Physics , 1999 .

[24]  Mieke Boon,et al.  How Science Is Applied in Technology , 2006 .

[25]  Tobias J. Hagge,et al.  Physics , 1929, Nature.

[26]  Eddie Norman.  Advanced Design and Technology , 1990 .

[27]  David Chiang,et al.  Statistical Parsing with an Automatically-Extracted Tree Adjoining Grammar , 2000, ACL.

[28]  A. Fine,et al.  The Dappled World , 2000 .

[29]  Ori Belkind,et al.  International Studies in the Philosophy of Science , 2007 .

[30]  Margaret Morrison,et al.  Models as Mediating Instruments , 1999 .

[31]  Michael Heidelberger,et al.  Applying Models in Fluid Dynamics , 2006 .

[32]  C. Crowe,et al.  Engineering fluid mechanics , 1975 .

[33]  Sergio Montes,et al.  Hydraulics of open channel flow , 1998 .

[34]  Atro Voutilainen,et al.  A Parser as an Epistemic Artifact: A Material View on Models , 2003, Philosophy of Science.

[35]  T. N. Stevenson,et al.  Fluid Mechanics , 2021, Nature.

[36]  Khalil Sima'an,et al.  Data-Oriented Parsing , 2003 .

[37]  Janet L. Kolodner,et al.  Case-Based Reasoning , 1989, IJCAI 1989.

[38]  Michael Collins,et al.  Three Generative, Lexicalised Models for Statistical Parsing , 1997, ACL.

[39]  N. Cartwright.  Book review: introduction and reply to - the dappled world: a study of the boundaries of science , 2002 .

[40]  J. Bresnan.  Lexical-Functional Syntax , 2000 .

[41]  J. Bertin.  Engineering fluid mechanics , 1984 .

[42]  Rens Bod,et al.  A Unified Model of Structural Organization in Language and Music , 2002, J. Artif. Intell. Res..

[43]  G. Batchelor,et al.  An Introduction to Fluid Dynamics , 1968 .

[44]  W. Wundt,et al.  Logik : eine Untersuchung der Prinzipien der Erkenntnis und der Methoden wissenschaftlicher Forschung , 1906 .

[45]  Eugene Charniak,et al.  Tree-Bank Grammars , 1996, AAAI/IAAI, Vol. 2.

[46]  Rens Bod,et al.  Exemplar-based syntax: How to get productivity from examples , 2006 .

[47]  M. Heidelberger.  Models in Fluid Dynamics , 2004 .

[48]  Beatrice Santorini,et al.  Building a Large Annotated Corpus of English: The Penn Treebank , 1993, CL.

[49]  Michael Collins,et al.  New Ranking Algorithms for Parsing and Tagging: Kernels over Discrete Structures, and the Voted Perceptron , 2002, ACL.

[50]  Jaime G. Carbonell,et al.  Derivational Analogy in PRODIGY: Automating Case Acquisition, Storage, and Utilization , 1993, Machine Learning.

[51]  Margaret Morrison.  Applying Science and Applied Science: What’s the Difference? , 2006 .

[52]  L.W.M. Bod,et al.  Grammaticality, Robustness and specificity in a Probabilistic Approach to Lexical Functional Analysis , 1998 .