human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "strong equivalence for lpmln programs"):
  Abstract: Strong equivalence is a well-studied and important concept in answer set programming (ASP). $\rm LP^{MLN}$ is a probabilistic extension of answer set programs with the weight scheme adapted from Markov Logic. Because of the semantic differences, strong equivalence for ASP does not simply carry over to $\rm LP^{MLN}$. I study the concept of strong equivalence in $\rm LP^{MLN}$ with the goal of extending strong equivalence to $\rm LP^{MLN}$ programs. My study shows that the verification of strong equivalence in $\rm LP^{MLN}$ can be reduced to equivalence checking in classical logic plus weight consideration.The result allows us to leverage an answer set solver for checking strong equivalence in $\rm LP^{MLN}$. Furthermore, this study also suggests us a few reformulations of the $\rm LP^{MLN}$ semantics using choice rules, logic of here and there, and the second-order logic. I will present my work result of strong equivalence for $\rm LP^{MLN}$ and talk about my next steps for research: one is approximately strong equivalence, and another is the integration of fuzzy logic with neural network.

Includes members:
  Member "weight learning in a probabilistic extension of answer set programs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the strong equivalences for lpmln programs")
  Member "a probabilistic extension of action language bc":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "bridging commonsense reasoning and probabilistic planning via a probabilistic action language")
  Member "computing lpmln using asp and mln solvers":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "bridging commonsense reasoning and probabilistic planning via a probabilistic action language")
  Member "logic tensor networks for semantic image interpretation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "analyzing differentiable fuzzy logic operators")
  Member "tensorlog a differentiable deductive database":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "inductive relation prediction by subgraph reasoning")
  Member "probabilistic reasoning with answer sets":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "semiring programming a declarative framework for generalized sum product problems")
  Member "propositional theories are strongly equivalent to logic programs":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "implementing dynamic answer set programming")
  Member "diagnostic reasoning with a prolog":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "restkb a library of commonsense knowledge about dining at a restaurant")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.LO(Logic in Computer Science)