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For AGI robots we consider the 4-valued Belnap's bilattice of truth-values with knowledge ordering as well, where the value "unknown" is the bottom value, the sentences with this value are indeed unknown facts, that is, the missed knowledge in the AGI robots. Thus, these unknown facts are not part of the robot's knowledge database, and by learn through input and experiences, the robot's knowledge would be naturally expanded over time.
Consequently, this phenomena can be represented by the Closed Knowledge Assumption and Logic Inference provided by this paper.
Moreover, the truth-value "inconsistent", which is the top value in the knowledge ordering of Belnap's bilattice, is necessary for strong-AI robots to be able to support such inconsistent information and paradoxes, like Liar paradox, during deduction processes.
| Comments: | 32 pages. arXiv admin note: substantial text overlap with arXiv:2508.02774 |
| Subjects: | Logic in Computer Science (cs.LO); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2604.09567 [cs.LO] |
| (or arXiv:2604.09567v1 [cs.LO] for this version) | |
| https://doi.org/10.48550/arXiv.2604.09567 arXiv-issued DOI via DataCite |
From: Zoran Majkic [view email]
[v1]
Wed, 18 Feb 2026 21:57:15 UTC (95 KB)
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