Applications of circumscription to formalizing common-sense knowledge
Artificial Intelligence
Embracing causality in fault reasoning
Artificial Intelligence
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
| Hi-index | 0.00 |
Reasoning about causality is an interesting application area of formal nonmonotonic theories. Here we focus our attention on a certain aspect of causal reasoning, namely causal asymmetry. In order to provide a qualitative account of causal asymmetry, we present a justification-based approach that uses circumscription to obtain the minimality of causes. We define the notion of causal and evidential support in terms of a justification change with respect to a circumscriptive theory and show how the definition provides desirable interactions between causal and evidential support.