AI 2010: Advances in Artificial Intelligence: 23rd by Jiuyong Li

By Jiuyong Li

This publication constitutes the refereed complaints of the twenty third Australasian Joint convention on man made Intelligence, AI 2010, held in Adelaide, Australia, in December 2010. The fifty two revised complete papers awarded have been conscientiously reviewed and chosen from 112 submissions. The papers are equipped in topical sections on wisdom illustration and reasoning; info mining and information discovery; computer studying; statistical studying; evolutionary computation; particle swarm optimization; clever agent; seek and making plans; common language processing; and AI purposes.

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Extra info for AI 2010: Advances in Artificial Intelligence: 23rd Australasian Joint Conference, Adelaide, Australia, December 7-10, 2010. Proceedings

Example text

The same issue of the relevance arises when the doctor tries to determine the most effective medication. It can be seen that in regard to the class of problems where the ‘relevance’ and the ‘comparison of the shifts’ in strengths of beliefs are key issues the theory of κ-functions is the most suitable belief change theory. However, in the theory of κ-functions, the temporal element of belief is not explicitly represented. Temporal Belief-Change: κ-functions Approach 13 The doctor identifies the illness c1 and advises the medication m1 at time t2 and expects the patient to recover by time t3 .

There are extensions of belief update that employ ranking; we briefly touch on two in the section 5 [9,10]. In the AGM theory, beliefs have strengths associated with them, called epistemic entrenchment values. Although, the AGM revision can provide a distinction about the strongest believed illnesses, it cannot identify the most relevant illnesses in relation to the identified symptoms. The reason is that to establish the most relevant illness, we need to compare the differences of the strength of the believed illnesses before and after the inclusion of the new symptoms.

We substantiate this claim as follows. In section 2, we remarked that histories are analogous to the models in PLTL. Let us apply the κ-functions to the models in PLTL similar to how we applied κ-functions to the histories. Then, following the Spohn’s method by which he shows his usual conditionalization function is analogue to the AGM revision operation, we can show that the temporal conditionalization presented here is an AGM compatible belief change operation [7,11]. We do not show this claim formally due to (1) the space constraint and (2) that the traditional temporal logics are designed to express the general properties of a system where the specific instants are not relevant.

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