Seeking Explanations: Abduction in Logic, Philosophy of Science and Artificial Intelligence
Dissertation, Stanford University (
1997)
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Abstract
In this dissertation I study abduction, that is, reasoning from an observation to its possible explanations, from a logical point of view. This approach naturally leads to connections with theories of explanation in the philosophy of science, and to computationally oriented theories of belief change in Artificial Intelligence. ;Many different approaches to abduction can be found in the literature, as well as a bewildering variety of instances of explanatory reasoning. To delineate our subject more precisely, and create some order, a general taxonomy for abductive reasoning is proposed in chapter 1. Several forms of abduction are obtained by instantiating three parameters: the kind of reasoning involved , the kind of observation triggering the abduction , and the kind of explanations produced . In chapter 2, I choose a number of major variants of abduction, thus conceived, and investigate their logical properties. A convenient measure for this purpose are so-called 'structural rules' of inference. Abduction deviates from classical consequence in this respect, much like many current non-monotonic consequence relations and dynamic styles of inference. As a result we can classify forms of abduction by different structural rules. A more computational analysis of processes producing abductive inferences is then presented in chapter 3, using the framework of semantic tableaux. I show how to implement various search strategies to generate various forms of abductive explanations. ;Our eventual conclusion is that abductive processes should be our primary concern, with abductive inferences their secondary 'products'. Finally, chapter 4 is a confrontation of the previous analysis with existing themes in the philosophy of science and artificial intelligence. In particular, I analyse two well-known models for scientific explanation as forms of abduction. This then provides them with a structural logical analysis in the style of chapter 2. Moreover, I argue that abduction can model dynamics of belief revision in artificial intelligence. For this purpose, an extended version of the semantic tableaux of chapter 3 provides a new representation of the operations of expansion, and contraction