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Neural logic programs and neural nets

arXiv 2406.11888 ↗First posted 13 Jun 2024cs.LO cs.AI cs.LGcited by 0

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Abstract (arXiv)

Neural-symbolic integration aims to combine the connectionist subsymbolic with the logical symbolic approach to artificial intelligence. In this paper, we first define the answer set semantics of (boolean) neural nets and then introduce from first principles a class of neural logic programs and show that nets and programs are equivalent.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 6 of its 51 references that are in the map. First posted on arXiv 13 Jun 2024.

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References · 6

  1. 2021DeepStochLog: Neural Stochastic Logic Programmingcited by 58
  2. 2018Logic program proportionscited by 12
  3. 2020Sequential composition of propositional logic programscited by 5
  4. 2021Sequential composition of answer set programscited by 5
  5. 2022Proportoidscited by 4
  6. 2020Fixed Point Semantics for Stream Reasoningcited by 3

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