@article{DBLP:journals/amai/EiterEFS07,
  author    = {Thomas Eiter and
               Esra Erdem and
               Michael Fink and
               J{\'a}n Senko},
  title     = {Comparing action descriptions based on semantic preferences},
  journal   = {Annals of Mathematics and Artificial Intelligence},
  volume    = {50},
  number    = {3-4},
  year      = {2007},
  pages     = {273-304},
  ee        = {http://dx.doi.org/10.1007/s10472-007-9077-y},
  bibsource = {DBLP, http://dblp.uni-trier.de},
  abstract  = {The focus of this paper is on action domain descriptions whose meaning can be 
represented by transition diagrams. We introduce several semantic measures to 
compare such action descriptions, based on preferences over possible states of 
the world and preferences over some given conditions (observations, assertions, 
etc.) about the domain, as well as the probabilities of possible transitions. 
This preference information is used to assemble a weight which is assigned to an 
action description. As applications of this approach, we study updating action 
descriptions and identifying elaboration tolerant action descriptions, with 
respect to some given conditions. With a semantic approach based on preferences, 
not only, for some problems, we get more plausible solutions, but also, for some 
problems without any solutions due to too strong conditions, we can identify 
which conditions to relax to obtain a solution. We further study computational 
issues, and give a characterization of the computational complexity of computing 
the semantic measures.
},
  
}

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