Space and time has been integrated into three qualitative models in this article: a qualitative motion model which integrates topology and time, a qualitative velocity model in 2-D and a qualitative velocity model in 3-D. The integration has been accomplished thanks to the definition of an approach with the following three steps: (1) the definition of the algebra of the spatial aspect to be integrated. The representation of each aspect is seen as an instance of the Constraint Satisfaction Problem (CSP); (2) the definition of the Basic Step of the Inference Process (BSIP) for each spatial aspect to be integrated. In general, the BSIP consists on given two relationships which relate three objects A, B, and C (one object is shared among the two relationships, for instance B), we will find the third relationship between objects A and C; and (3) the definition of the Full Inference Process (FIP) for each spatial aspect to be integrated which consists on repeating the BSIP as many times as possible with the initial information and the information provided by some BSIP, until no more information can be inferred. The corresponding algorithm is solved using Constraint Logic Programming extended with Constraint Handling Rules (CLP+CHRs) as tool

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Space and time has been integrated into three qualitative models in this article: a qualitative motion model which integrates topology and time, a qualitative velocity model in 2-D and a qualitative velocity model in 3-D. The integration has been accomplished thanks to the definition of an approach with the following three steps: (1) the definition of the algebra of the spatial aspect to be integrated. The representation of each aspect is seen as an instance of the Constraint Satisfaction Problem (CSP); (2) the definition of the Basic Step of the Inference Process (BSIP) for each spatial aspect to be integrated. In general, the BSIP consists on given two relationships which relate three objects A, B, and C (one object is shared among the two relationships, for instance B), we will find the third relationship between objects A and C; and (3) the definition of the Full Inference Process (FIP) for each spatial aspect to be integrated which consists on repeating the BSIP as many times as possible with the initial information and the information provided by some BSIP, until no more information can be inferred. The corresponding algorithm is solved using Constraint Logic Programming extended with Constraint Handling Rules (CLP+CHRs) as tool

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Universidad Autónoma del Estado de México
Sistema de Información Científica Redalyc ®