An abstract, argumentation-theoretic approach to default reasoning
Artificial Intelligence
Causality in commonsense reasoning about actions
Causality in commonsense reasoning about actions
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AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
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AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
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International Journal of Knowledge-based and Intelligent Engineering Systems
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CLIMA'09 Proceedings of the 10th international conference on Computational logic in multi-agent systems
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Journal of Intelligent Information Systems
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Applied Intelligence
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The language Ɛ for reasoning about actions and change can be translated into an argumentation framework. In this paper, we extend this translation of the basic language and showh ow it can, together with methods from abduction, form the basis for a principled implementation of Ɛ. The extension we have considered concerns the addition of new type of sentences in the language as well as allowing theories where the narrative of events given is incomplete. A system, called Ɛ-RES, is developed within the argumentation framework of Logic Programming without Negation as Failure (LPwNF). This can support directly a variety of modes of common sense reasoning such as: default persistence in credulous or sceptical form, assimilation of observations and their diagnosis possibly under incomplete information, as well as combinations of these. To improve the efficiency of the system we have considered the integration of a SAT solver within the LPwNF computation, to carry out the of validating the time universal constraints imposed by ramification statements.