Conditional logic of actions and causation
Artificial Intelligence, ISSN: 0004-3702, Vol: 157, Issue: 1, Page: 239-279
2004
- 30Citations
- 29Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
In this paper we present a new approach to reasoning about actions and causation which is based on a conditional logic. The conditional implication is interpreted as causal implication. This makes it possible to formalize in a uniform way causal dependencies between actions and their immediate and indirect effects. The proposed approach also provides a natural formalization of concurrent actions and of the dependency (and independency) relations between actions. The properties of causality are formalized as axioms of the conditional connectives and a non-monotonic (abductive) semantics is adopted for dealing with the frame problem.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0004370204000621; http://dx.doi.org/10.1016/j.artint.2004.04.009; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=2942693734&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S0004370204000621; https://api.elsevier.com/content/article/PII:S0004370204000621?httpAccept=text/xml; https://api.elsevier.com/content/article/PII:S0004370204000621?httpAccept=text/plain; https://dx.doi.org/10.1016/j.artint.2004.04.009
Elsevier BV
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