Forthcoming Papers

2002 Artificial Intelligence  
Binary vs. non-binary constraints There are two well known transformations from non-binary constraints to binary constraints applicable to constraint satisfaction problems (CSPs) with finite domains: the dual transformation and the hidden (variable) transformation. We perform a detailed formal comparison of these two transformations. Our comparison focuses on two backtracking algorithms that maintain a local consistency property at each node in their search tree: the forward checking and
more » ... ning arc consistency algorithms. We first compare local consistency techniques such as arc consistency in terms of their inferential power when they are applied to the original (non-binary) formulation and to each of its binary transformations. For example, we prove that enforcing arc consistency on the original formulation is equivalent to enforcing it on the hidden transformation. We then extend these results to the two backtracking algorithms. We are able to give either a theoretical bound on how much one formulation is better than another, or examples that show such a bound does not exist. For example, we prove that the performance of the forward checking algorithm applied to the hidden transformation of a problem is within a polynomial bound of the performance of the same algorithm applied to the dual transformation of the problem. Our results can be used to help decide if applying one of these transformations to all (or part) of a constraint satisfaction model would be beneficial.  2002 Published by Elsevier Science B.V. C. Bettini, X.S. Wang and S. Jajodia, Solving multi-granularity temporal constraint networks Many problems in scheduling, planning, and natural language understanding have been formulated in terms of temporal constraint satisfaction problems (TCSP). These problems have been extensively investigated in the AI literature providing effective solutions for some fragments of the general model. Independently, there has been an effort in the data and knowledge management research community for the formalization of the concept of time granularity and for its applications. This paper considers a framework for integrating the notion of time granularity into TCSP, and investigates the problems of consistency and network solution, which, in this context, involve complex manipulation of the periodic sets representing time granularities. A sound and complete algorithm for consistency checking and for deriving a solution is presented. The paper also investigates the algorithm's computational complexity and several optimization techniques specific to the multi-granularity context. An application to e-commerce workflows illustrates the benefits of the framework and the need for specific reasoning tools.  2002 Published by Elsevier Science B.V. 0004-3702/2002 Published by Elsevier Science B.V. PII: S 0 0 0 4 -3 7 0 2 ( 0 2 ) 0 0 2 8 1 -3
doi:10.1016/s0004-3702(02)00281-3 fatcat:6gorcgplazbgtpkw4sdr7oajwa