ML Anthology

A Calculus for Logical Clustering

Shuo Bai
ALT 1994 pp. 56-63
doi:10.1007/3-540-58520-6_53 /alt/1994/bai1994alt-calculus/

Abstract

A formal calculus, LC , for logical clustering is proposed in this paper. In addition to conventional first-order logic, a nonmonotonic inference rule for logical clustering is introduced, such that typical forms of induction and analogy are uniformly treated in our theory. Our result shows that the nature of induction and analogy are both “information compression”, that is, the merging of indistinguishable logical symbols. Argumentation games for the implementation of LC are also discussed in this paper.

PDF ALT Semantic Scholar

Cite

Text

Bai. "A Calculus for Logical Clustering." International Conference on Algorithmic Learning Theory, 1994. doi:10.1007/3-540-58520-6_53

Markdown

[Bai. "A Calculus for Logical Clustering." International Conference on Algorithmic Learning Theory, 1994.](https://mlanthology.org/alt/1994/bai1994alt-calculus/) doi:10.1007/3-540-58520-6_53

BibTeX

@inproceedings{bai1994alt-calculus,
  title     = {{A Calculus for Logical Clustering}},
  author    = {Bai, Shuo},
  booktitle = {International Conference on Algorithmic Learning Theory},
  year      = {1994},
  pages     = {56-63},
  doi       = {10.1007/3-540-58520-6_53},
  url       = {https://mlanthology.org/alt/1994/bai1994alt-calculus/}
}