Yu Wang
ABSTRACT
In order to characterize causal relation, different scholars have studied it from multiple perspectives. In the field of logic, the causal theory proposed by Alexander elaborated the causal relationship from the perspective of nonmonotonic reasoning. The Horn causal theory and the concept of equivalence relationship are defined in his article, but the author did not give the determination method of equivalence relationship. In order to make up for this deficiency, this paper introduces the concept of bisimulation to describe the equivalence relation between Horn causal theories and proves the consistency between bisimulation relation and the equivalence of models. Then the corresponding algorithm is proposed to determine the equivalence. An example is also given to illustrate the application of this method in determining equivalence relationship.
- Ji J, Chen X. A weighted causal theory for acquiring and utilizing open knowledge. International Journal of Approximate Reasoning, 2014.Google Scholar
Digital Library
- Judea Pearl. Causality: models, reasoning, and inference. Cambridge University Press, 2000.Google Scholar
- J Peters, D Janzing, Bernhard Schölkopf. Elements of Causal Inference - Foundations and Learning Algorithms .Cambridge:MIT Press, 2017.Google ScholarDigital Library
- Shimizu S, Inazumi T, Sogawa Y, DirectLiNGAM: A direct method for learning a linear non-Gaussian structural equation model. Journal of Machine Learning Research, 2011, 12(2):1225-1248.Google ScholarDigital Library
- Ruichu Cai, Wei chen, Kun Zhang, A review of causal relationship discovery based on non time series observation data .Chinese Journal of Computers, 2017.Google Scholar
- N. McCain, H. Turner, Causal theories of action and change, in: Proceedings of the 14th National Conference on Artificial Intelligence (AAAI-97), 1997, pp. 460-465.Google ScholarDigital Library
- Giunchiglia, E, Lee, Nonmonotonic causal theories. Artificial Intelligence Amsterdam Elsevier, 2004.Google ScholarDigital Library
- Bochman A. A causal approach to nonmonotonic reasoning.Artificial intelligence, 2004, pp. 105-143.Google Scholar
- http://www.causality.inf.ethz.ch/.Google Scholar
- Spirtes P , Glymour C , Scheines R . Causation, Prediction, and Search, 2nd Edition.Pattern Recognition & Image Analysis-iberian Conference. 2001.Google Scholar
- Li Y, Wang T, Yue D P. An integrated method for causality structure and hidden cause discovery.2014 International Conference on Computer Science and Systems Engineering CSSE2014. 0.Google Scholar
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