Conditional entailment: bridging two approaches to default reasoning
Artificial Intelligence
A logic of knowledge and justified assumptions
Artificial Intelligence
Strongly equivalent logic programs
ACM Transactions on Computational Logic (TOCL) - Special issue devoted to Robert A. Kowalski
Strong Equivalence for Logic Programs and Default Theories (Made Easy)
LPNMR '01 Proceedings of the 6th International Conference on Logic Programming and Nonmonotonic Reasoning
A New Logical Characterisation of Stable Models and Answer Sets
NMELP '96 Selected papers from the Non-Monotonic Extensions of Logic Programming
Equilibria in heterogeneous nonmonotonic multi-context systems
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Sound and complete inference rules for SE-consequence
Journal of Artificial Intelligence Research
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
A faithful integration of description logics with logic programming
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Minimal and absent information in contexts
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
LPNMR'07 Proceedings of the 9th international conference on Logic programming and nonmonotonic reasoning
Answer sets for propositional theories
LPNMR'05 Proceedings of the 8th international conference on Logic Programming and Nonmonotonic Reasoning
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In this paper, we propose a logic framework for meta level reasoning as well as default reasoning in a general sense, based on an arbitrary underlying logic. In this framework, meta level reasoning is the task of how to deduce new meta level rules by giving a set of rules, whilst default reasoning is the problem of what are the possible candidate beliefs by giving them. We define the semantics for both meta level reasoning and default reasoning and investigate their relationships. We show that this framework captures various nonmonotonic paradigms, including answer set programming, default logic, contextual default reasoning, by applying the underlying logic to different classes. Finally, we show that this framework can be reduced into answer set programming.