Abstract
Analogical reasoning can be understood as a kind of resemblance of one thing to another, thus assigning properties from one context to another. The key idea is to use similarity information to support an inference which cannot be deductively inferred. In this paper, we present a formal and intuitive framework of this phenomena using an argument-based logic-programming-like language. A proof theory of our system is stated in the dialectical style, where a proof takes the form of dialogue between a proponent and an opponent of an argument. We also discuss how the proposed framework can be fine tuned for optimistic analogical reasoning and pessimistic analogical reasoning. Finally, we discuss a design sketch of our proposed analogical reasoner called Analogist.
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Notes
- 1.
- 2.
When \(x = 1\), we may remove it.
- 3.
When \(w = 1\), we may remove it.
- 4.
The precise definition of t-norm is given later.
- 5.
We may employ the notion of \(\overset{\pi }{\sim }_\mathcal {T} \) to obtain 0.8 from realistic ontologies.
- 6.
Later, this definition is used by Definition 11 for comparing between rebuttal attacks.
- 7.
For the sake of succinctness, \(\cdot ^\mathsf {D}\) (and \(\cdot ^\mathsf {S}\)) indicates a duplicated set of defeasible rules (and similarity rules, respectively) from a specified argument structure.
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Acknowledgments
This research is supported by JAIST, NECTEC, and SIIT under the dual doctoral degree program; and is partly supported by CILS of Thammasat University and the NRU project of Thailand Office of Higher Education Commission.
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Racharak, T., Tojo, S., Hung, N.D., Boonkwan, P. (2017). Argument-Based Logic Programming for Analogical Reasoning. In: Kurahashi, S., Ohta, Y., Arai, S., Satoh, K., Bekki, D. (eds) New Frontiers in Artificial Intelligence. JSAI-isAI 2016. Lecture Notes in Computer Science(), vol 10247. Springer, Cham. https://doi.org/10.1007/978-3-319-61572-1_17
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