K3, L3, LP, RM3, A3, FDE: How to Make Many-Valued Logics Work for You
November 15, 2017 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Allen P. Hazen, Francis Jeffry Pelletier
arXiv ID
1711.05816
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.LO
Citations
7
Venue
arXiv.org
Last Checked
4 months ago
Abstract
We investigate some well-known (and a few not-so-well-known) many-valued logics that have a small number (3 or 4) of truth values. For some of them we complain that they do not have any \emph{logical} use (despite their perhaps having some intuitive semantic interest) and we look at ways to add features so as to make them useful, while retaining their intuitive appeal. At the end, we show some surprising results in the system FDE, and its relationships with features of other logics. We close with some new examples of "synonymous logics." An Appendix contains a natural deduction system for our augmented FDE, and proofs of soundness and completeness.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Artificial Intelligence
π
π
The Cartographer
R.I.P.
π»
Ghosted
Explanation in Artificial Intelligence: Insights from the Social Sciences
R.I.P.
π»
Ghosted
Federated Machine Learning: Concept and Applications
R.I.P.
π»
Ghosted
Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR
R.I.P.
π»
Ghosted
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
R.I.P.
π»
Ghosted
Rainbow: Combining Improvements in Deep Reinforcement Learning
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted