Logical and Computational Aspects of Model-Based Reasoning

by Magnani, Lorenzo; Nersessian, Nancy J.; Pizzi, Claudio

• ISBN13: 9781402007125
• ISBN10: 1402007124
• Format: Hardcover
• Copyright: 2002-12-01
• Publisher: Kluwer Academic Pub

Summary

This volume is based on the papers that were presented at the International Conference 'Model-Based Reasoning: Scientific Discovery, Technological Innovation, Values' (MBR'01), held at the Collegio Ghislieri, University of Pavia, Pavia, Italy, in May 2001. The previous volume Model-Based Reasoning in Scientific Discovery, edited by L. Magnani, N.J. Nersessian, and P. Thagard (Kluwer Academic/Plenum Publishers, New York, 1999; Chinese edition, China Science and Technology Press, Beijing, 2000), was based on the papers presented at the first 'model-based reasoning' international conference, held at the same venue in December 1998. The presentations given at the Conference explore how scientific thinking uses models and exploratory reasoning to produce creative changes in theories and concepts. Some address the problem of model-based reasoning in ethics, especially pertaining to science and technology, and stress some aspects of model-based reasoning in technological innovation. The study of diagnostic, visual, spatial, analogical, and temporal reasoning has demonstrated that there are many ways of performing intelligent and creative reasoning that cannot be described with the help only of traditional notions of reasoning such as classical logic. Understanding the contribution of modeling practices to discovery and conceptual change in science requires expanding scientific reasoning to include complex forms of creative reasoning that are not always successful and can lead to incorrect solutions. The study of these heuristic ways of reasoning is situated at the crossroads of philosophy, artificial intelligence, cognitive psychology, and logic; that is, at the heart of cognitive science. There are several key ingredients common to the various forms of model-based reasoning. The term 'model' comprises both internal and external representations. The models are intended as interpretations of target physical systems, processes, phenomena, or situations. The models are retrieved or constructed on the basis of potentially satisfying salient constraints of the target domain. Moreover, in the modeling process, various forms of abstraction are used. Evaluation and adaptation take place in light of structural, causal, and/or functional constraints. Model simulation can be used to produce new states and enable evaluation of behaviors and other factors. The various contributions of the book are written by interdisciplinary researchers who are active in the area of creative reasoning in science and technology, and are logically and computationally oriented: the most recent results and achievements about the topics above are illustrated in detail in the papers.

Table of Contents

Logical Aspects of Model-Based Reasoning	1	(199)
A Case Study of the Design and Implementation of Heterogeneous Reasoning Systems	3	(18)
Nik Swoboda
Gerard Allwein
Background	3	(1)
Overview	4	(2)
Some preliminary definitions	6	(3)
A framework for heterogeneous reasoning	9	(1)
Defining the notion of recasting for Euler/Venn and FOL	10	(6)
The implementation	16	(5)
A Logical Approach to the Analysis of Metaphors	21	(18)
Isabel D'Hanis
Introduction	21	(1)
The interactionist view as a basis for a metaphor theory	22	(2)
Some problems with the basic formulation of the interactionist view	24	(3)
The advantages of adaptive logics	27	(1)
ALM, an adaptive logic for metaphors	28	(7)
Conclusions	35	(4)
Ampliative Adaptive Logics and the Foundation of Logic-Based Approaches to Abduction	39	(34)
Joke Meheus
Liza Verhoeven
Maarten Van Dyck
Dagmar Provijn
Aim and survey	40	(2)
Why the reconstruction is important	42	(2)
Main characteristics of abductive reasoning	44	(3)
The general format	47	(1)
Introducting the dynamics	48	(2)
The logics MA 1 and CP 1	50	(6)
Generalizing to the inconsistent case	56	(4)
The logics MA 2 and CP 2	60	(2)
Two examples from the history of astronomy	62	(6)
Some alternatives	68	(1)
Conclusion	69	(4)
Diagrammatic Inference and Graphical Proof	73	(20)
Luis A. Pineda
Introduction	73	(2)
Abstraction markers	75	(5)
Notational keys	80	(2)
The syntactic effect and reinterpretation	82	(2)
A diagrammatic inference scheme	84	(5)
Global reinterpretation	89	(4)
A Logical Analysis of Graphical Consistency Proofs	93	(24)
Atsushi Shimojima
Introduction	93	(3)
Examples	96	(4)
Analysis	100	(5)
Physical on-site inferences	105	(9)
Summary	114	(3)
Adaptive Logics for Non-Explanatory and Explanatory Diagnostic Reasoning	117	(26)
Dagmar Provijn
Erik Weber
Introduction	117	(1)
Non-explanatory and explanatory diagnosis for faults in systems	118	(4)
Adaptive logics	122	(2)
An adaptive logic for non-explanatory diagnostic reasoning	124	(3)
The dynamic proof theory of Dnexp	127	(2)
An illustration of Dnexp	129	(1)
Formal analysis of weak explanatory diagnostic reasoning	130	(3)
Formal analysis of strong explanatory diagnostic reasoning	133	(1)
An adaptive logic for explanatory diagnostic reasoning	134	(3)
The dynamic proof theory of Dexp	137	(2)
An illustration of Dexp	139	(4)
Model-Guided Proof Planning	143	(20)
Seungyeob Choi
Manfred Kerber
Introduction	143	(3)
Proof planning as a way of reasoning	146	(4)
Model-based reasoning	150	(4)
Semantic restriction and selection of methods	154	(4)
Implementation and initial results	158	(2)
Conclusion	160	(3)
Degrees of Abductive Boldness	163	(18)
Isabella C. Burger
Johannes Heidema
Introduction: Cautions Inference and bold conjecture	163	(2)
Abduction as defeasible inference	165	(3)
Merging inference and conjecture	168	(5)
Abduction via power relations	173	(8)
Scientific Explanation and Modified Semantic Tableaux	181	(18)
Angel Nepomuceno-Fernandez
Introduction	181	(1)
Modified semantic tableaux	182	(2)
Scientific explanation	184	(6)
Conclusions	190	(1)
Appendix	191	(8)
Computational Aspects of Model-Based Reasoning	199	(132)
Computational Discovery of Communicable Knowledge	201	(26)
Pat Langley
Jeff Shrager
Kazumi Saito
Introduction	201	(1)
Paradigms for computational discovery	202	(4)
Revising regulatory models in microbiology	206	(5)
Revising quantitative models in Earth science	211	(8)
Related research on computational discovery	219	(2)
Concluding remarks	221	(6)
Encoding and Using Domain Knowledge on Population Dynamics for Equation Discovery	227	(22)
Saso Dzeroski
Ljupco Todorovski
Introduction	227	(1)
Population dynamics modeling	228	(6)
Equation discovery	234	(3)
The equation discovery system Lagramge 2.0	237	(2)
Experiments	239	(4)
Discussion	243	(6)
Appendix: The Prolog program for transforming the population dynamics domain knowledge into grammar form	245	(4)
Reasoning about Models of Nonlinear Systems	249	(24)
Reinhard Stolle
Matthew Easley
Elizabeth Bradley
Reasoning about nonlinear system identification	250	(6)
Automated modeling and scientific discovery	256	(4)
Representations for model building	260	(4)
Orchestrating reasoning about models	264	(4)
Conclusion	268	(5)
Model-Based Diagnosis of Dynamic Systems: Systematic Conflict Generation	273	(20)
Bartlomiej Gorny
Antoni Ligeza
Introduction	273	(2)
Consistency-based diagnosis: Reiter's Theory	275	(1)
Causal graph	276	(1)
Graphical notation	277	(1)
Problem formulation	277	(1)
Strategy for conflicts calculation and diagnoses generation	278	(1)
An approach to systematic conflict generation	279	(1)
Potential conflict structure	280	(2)
An outline of algorithmic approach	282	(1)
Diagnoses calculation - elements of algebraic approach	283	(3)
An example	286	(3)
Conclusions	289	(4)
Modeling Through Human-Computer Interactions and Mathematical Discourse	293	(20)
Germana Menezes da Nobrega
Philippe Malbos
Jean Sallantin
Introducing φ-calculus	295	(5)
An experiment in LAW	300	(1)
A formal system for φ-calculus	301	(7)
Conclusion	308	(5)
Combining Strategy and Sub-models for the Objectified Communication of Research Programs	313	(18)
Ekkehard Finkeissen
Scientific objectification of decision-making	314	(3)
Strategy: Superior structure of discrete decisions	317	(5)
Embedding of sub-models into the decision-structure	322	(2)
Imbedding of intra-individual preferences into the decision model	324	(2)
Generating individual problem solutions with the decision model	326	(2)
Summary and prospects	328	(3)
Subject Index	331	(6)
Author Index	337