Logical and Computational Aspects of Model-Based Reasoning

L. Magnani, Nancy Nersessian, Claudio Pizzi

Springer Science & Business Media, Sep 30, 2002 - Mathematics - 342 pages

Information technology has been, in recent years, under increasing commercial pressure to provide devices and systems which help/ replace the human in his daily activity. This pressure requires the use of logic as the underlying foundational workhorse of the area. New logics were developed as the need arose and new foci and balance has evolved within logic itself. One aspect of these new trends in logic is the rising impor tance of model based reasoning. Logics have become more and more tailored to applications and their reasoning has become more and more application dependent. In fact, some years ago, I myself coined the phrase "direct deductive reasoning in application areas", advocating the methodology of model-based reasoning in the strongest possible terms. Certainly my discipline of Labelled Deductive Systems allows to bring "pieces" of the application areas as "labels" into the logic. I therefore heartily welcome this important book to Volume 25 of the Applied Logic Series and see it as an important contribution in our overall coverage of applied logic.

Contents

• A Case Study of the Design and Implementation of Heterogeneous Reasoning Systems: 3
• Overview: 4
• Some preliminary definitions: 6
• A framework for heterogeneous reasoning: 9
• Defining the notion of recasting for EulerVenn and FOL: 10
• The implementation: 16
• A Logical Approach to the Analysis of Metaphors: 21
• The interactionist view as a basis for a metaphor theory: 22
• Some problems with the basic formulation of the interactionist view: 24
• The advantages of adaptive logics: 27
• ALM an adaptive logic for metaphors: 28
• Conclusions: 35
• Ampliative Adaptive Logics and the Foundation of LogicBased: 37
• Approaches to Abduction: 39
• Joke Meheus Liza Verhoeven Maarten Van Dyck Dagmar Provijn 1 Aim and survey: 40
• Why the reconstruction is important: 42
• Main characteristics of abductive reasoning: 44
• The general format: 47
• Introducing the dynamics: 48
• The logics MAI and CP1: 50
• Generalizing to the inconsistent case: 56
• The logics MA2 and CP2: 60
• Two examples from the history of astronomy: 62
• Some alternatives: 68
• Conclusion: 69
• Diagrammatic Inference and Graphical Proof: 73
• Abstraction markers: 75
• Notational keys: 80
• The syntactic effect and reinterpretation: 82
• A diagrammatic inference scheme: 84
• Global reinterpretation: 89
• A Logical Analysis of Graphical Consistency Proofs: 93
• Examples: 96
• Analysis: 100
• Physical onsite inferences: 105
• Summary: 114
• Adaptive Logics for NonExplanatory and Explanatory Diagnostic Reasoning: 117
• Nonexplanatory and explanatory diagnosis for faults in sys tems: 118
• Adaptive logics: 122
• An adaptive logic for nonexplanatory diagnostic reasoning: 124
• The dynamic proof theory of DnexP: 127
• An illustration of DnexP: 129
• Formal analysis of weak explanatory diagnostic reasoning: 130
• Formal analysis of strong explanatory diagnostic reasoning: 133
• An adaptive logic for explanatory diagnostic reasoning: 134
• The dynamic proof theory of Deip: 137
• An illustration of Dexp: 139
• ModelGuided Proof Planning: 143
• Proof planning as a way of reasoning: 146
• Modelbased reasoning: 150
• Semantic restriction and selection of methods: 154
• Implementation and initial results: 158
• Conclusion: 160
• Degrees of Abductive Boldness: 163
• Abduction as defeasible inference: 165
• Merging inference and conjecture: 168
• Abduction via power relations: 173
• Scientific Explanation and Modified Semantic Tableaux: 181
• Modified semantic tableaux: 182
• Scientific explanation: 184
• Conclusions: 190
• Appendix: 191
• Computational Aspects of ModelBased Reasoning: 199
• Computational Discovery of Communicable Knowledge: 201
• Paradigms for computational discovery: 202
• Revising regulatory models in microbiology: 206
• Revising quantitative models in Earth science: 211
• Related research on computational discovery: 219
• Concluding remarks: 221
• Encoding and Using Domain Knowledge on Population Dynamics for Equation Discovery: 227
• Population dynamics modeling: 228
• Equation discovery: 234
• The equation discovery system LAGRAMGB 2 0: 237
• Experiments: 239
• Discussion: 243
• The Prolog program for transforming the population dynamics domain knowledge into grammar form: 245
• Reasoning about Models of Nonlinear Systems: 249
• Reinhard Stolle Matthew Easley Elizabeth Bradley 1 Reasoning about nonlinear system identification: 250
• Automated modeling and scientific discovery: 256
• Representations for model building: 260
• Orchestrating reasoning about models: 264
• Conclusion: 268
• Systematic Conflict Generation: 273
• Reiters Theory: 275
• Causal graph: 276
• Graphical notation: 277
• Strategy for conflicts calculation and diagnoses generation: 278
• An approach to systematic conflict generation: 279
• Potential conflict structure: 280
• An outline of algorithmic approach: 282
• Diagnoses calculation elements of algebraic approach: 283
• An example: 286
• Conclusions: 289
• Modeling Through HumanComputer Interactions and Mathematical Discourse: 293
• Germane Menezes da Nobrega Philippe Malbos Jean Sallantin 1 Introducing yjcalculus: 295
• An experiment in LAW: 300
• Combining Strategy and Submodels for the Objectified Communication: 313
• Subject Index: 331

Bibliographic information

• Title: Logical and Computational Aspects of Model-Based Reasoning; Volume 25 of Applied Logic Series
• Editors: L. Magnani, Nancy Nersessian, Claudio Pizzi
• Edition: illustrated
• Publisher: Springer Science & Business Media, 2002
• ISBN: 1402007124, 9781402007125
• Length: 342 pages
• Subjects: Computers / Intelligence (AI) & Semantics; Mathematics / General; Mathematics / History & Philosophy; Mathematics / Logic; Philosophy / Logic