Proceedings

Determining Explanations using Transmutations

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Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence. Knowledge Representation. Pages 822-828.

Abstract

Intelligent Information systems do not usually possess complete information about the world with which they interact. The AGM paradigm has become one of the standard frameworks for modeling changes to repositories of information. Its principal constructions for change operators rely on some form of underlying preference relation. The process of changing such a preference relation is known as a transmutation. Spohn's conditionalization can be interpreted as a transmutation that imposes a relative minimal change. A transmutation based on an absolute minimal change is an adjustment. In this paper we develop a notion of explanation using transmutations of information systems. Following Gardenfors lead we recast Spohn's notion of reason for within the general setting of transmutations and extend this to characterize most plausible explanations. We also investigate the relationship between explanation based on abduction and Spohnian reasons based on adjustments. Finally, and rather surprisingly, we identify explicit conditions that characterize the various forms of explanations identified by Boutilier and Becher using Spohnian reasons.

Mary-Anne Williams, Maurice Pagnucco, Norman Y. Foo, and Brailey Sims. 1995. Determining Explanations using Transmutations. In Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, IJCAI-95. IJCAI, 822–828. https://ijcai.org/proceedings/1995/107
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