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IRIT

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AAAI Conference 1999 Conference Paper

A Sequential Reversible Belief Revision Method Based on Polynomials

Salem Benferhat
Didier Dubois
IRIT
Université Paul Sabatier; Odile Papini
LIM
Université de la Méditerranée

This paper deals with iterated belief changeand proposesa drastic revisionrule that modifiesa plausibility ordering of interpretations in such a waythat anyworld wherethe input observartion holds is moreplausible that any world where it does not. This change nile makessense in a dynamiccontext where observations are received, andthe newerobservations are considered more plausible than older ones. It is shownhowto encode an epistemic state using polynomials equipped with the lexicographical ordering. This encodingmakes it very easy to implement anditerate the revision rule using simple operations on these polynomials. Moreover, polynomials allowto keeptrack of the sequenceof observations. Lastly, it is shown howto efficiently compute the revision rule at the syntactical level, whenthe epistemicstate is conciselyrepresentedby a prioritized belief base. Ourrevision rule is the mostdrastic one can think of, in accordancewith Darwiche and Pearl’s principles, and thus contrasts with the minimalchange rule called natural belief revision.

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AAAI Conference 1999 Conference Paper

Total Order Planning Is More Efficient than We Thought

Vincent Vidal
Pierre Régnier
IRIT
Paul Sabatier University

In this paper, we present VVPLAN, a planner based on a classical state space search algorithm. The language used for domain and problem representation is ADL (Pednault 1989). We have compared VVPLAN to UCPOP (Penberthy and Weld 1992)(Weld 1994), a planner that admits the same representation language. Our experiments prove that such an algorithm is often more efficient than a planner based on a search in the space of partial plans. This result is achieved as soon as we introduce in VVPLANs algorithm a loop test relating to previously visited states. In particular domains, VVPLAN can also outperform IPP (Koehler et al. 1997), which makes a planning graph analysis as GRAPHPLAN. We present here the details of our comparison with UCPOP, the results we obtain and our conclusions.

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