Marek＇s forward-chaining construction is one of the important techniques for investigating the non-monotonic reasoning. By introduction of consistency property over a logic program, they proposed a class of logic pro...Marek＇s forward-chaining construction is one of the important techniques for investigating the non-monotonic reasoning. By introduction of consistency property over a logic program, they proposed a class of logic programs, FC-normal programs, each of which has at least one stable model. However, it is not clear how to choose one appropriate consistency property for deciding whether or not a logic program is FC-normal. In this paper, we firstly discover that, for any finite logic programⅡ, there exists the least consistency property LCon（Ⅱ） overⅡ, which just depends onⅡitself, such that, Ⅱ is FC-normal if and only ifⅡ is FC-normal with respect to （w.r.t.） LCon（Ⅱ）. Actually, in order to determine the FC-normality of a logic program, it is sufficient to check the monotonic closed sets in LCon（Ⅱ） for all non-monotonic rules, that is LFC（Ⅱ）. Secondly, we present an algorithm for computing LFC（Ⅱ）. Finally, we reveal that the brave reasoning task and cautious reasoning task for FC-normal logic programs are of the same difficulty as that of normal logic programs.展开更多
计算树逻辑(computation tree logic,CTL)的范式在模型检测方法中具有重要意义,但基于广义可能性测度的计算树逻辑的范式尚未有系统研究。为了进一步完善广义可能性计算树(generalized possibilistic computation tree logic,GPo CTL)理...计算树逻辑(computation tree logic,CTL)的范式在模型检测方法中具有重要意义,但基于广义可能性测度的计算树逻辑的范式尚未有系统研究。为了进一步完善广义可能性计算树(generalized possibilistic computation tree logic,GPo CTL)理论,在现有的广义可能性计算树逻辑理论的基础上,参考经典计算树逻辑的范式,给出了广义可能性计算树逻辑的两种不同的范式——正态范式(positive normal form,PNF)和存在范式(existential normal form,ENF),及其对应的语构和语义解释。最后利用归纳假设法证明了任意的广义可能性计算树逻辑公式都有与之等价的PNF公式和ENF公式。展开更多
基金This work is partially supported by the National Natural Science Foundation of China under Grant No.60573009the Stadholder Foundation of Guizhou Province under Grant No.2005(212).
文摘Marek＇s forward-chaining construction is one of the important techniques for investigating the non-monotonic reasoning. By introduction of consistency property over a logic program, they proposed a class of logic programs, FC-normal programs, each of which has at least one stable model. However, it is not clear how to choose one appropriate consistency property for deciding whether or not a logic program is FC-normal. In this paper, we firstly discover that, for any finite logic programⅡ, there exists the least consistency property LCon（Ⅱ） overⅡ, which just depends onⅡitself, such that, Ⅱ is FC-normal if and only ifⅡ is FC-normal with respect to （w.r.t.） LCon（Ⅱ）. Actually, in order to determine the FC-normality of a logic program, it is sufficient to check the monotonic closed sets in LCon（Ⅱ） for all non-monotonic rules, that is LFC（Ⅱ）. Secondly, we present an algorithm for computing LFC（Ⅱ）. Finally, we reveal that the brave reasoning task and cautious reasoning task for FC-normal logic programs are of the same difficulty as that of normal logic programs.
文摘计算树逻辑(computation tree logic,CTL)的范式在模型检测方法中具有重要意义,但基于广义可能性测度的计算树逻辑的范式尚未有系统研究。为了进一步完善广义可能性计算树(generalized possibilistic computation tree logic,GPo CTL)理论,在现有的广义可能性计算树逻辑理论的基础上,参考经典计算树逻辑的范式,给出了广义可能性计算树逻辑的两种不同的范式——正态范式(positive normal form,PNF)和存在范式(existential normal form,ENF),及其对应的语构和语义解释。最后利用归纳假设法证明了任意的广义可能性计算树逻辑公式都有与之等价的PNF公式和ENF公式。
