Abstract
This paper discusses several key issues in temporal and causal inference in the context of AGI. The main conclusions are: (1) the representation of temporal information should take multiple forms; (2) classical conditioning can be carried out as temporal inference; (3) causal inference can be realized without a predefined causal relation.
Cite
CITATION STYLE
APA
Wang, P., & Hammer, P. (2015). Issues in temporal and causal inference. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9205, pp. 208–217). Springer Verlag. https://doi.org/10.1007/978-3-319-21365-1_22
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