human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "monte carlo tableau proof search"
  Abstract: We study Monte Carlo Tree Search to guide proof search in tableau calculi. This includes proposing a number of proof-state evaluation heuristics, some of which are learnt from previous proofs. We present an implementation based on the leanCoP prover. The system is trained and evaluated on a large suite of related problems coming from the Mizar proof assistant, showing that it is capable to find new and different proofs.

Connected through hyperedge HE-1 (induced by source paper "enigma ng efficient neural and gradient boosted inference guidance for e"):
  with members:
    - "atpboost learning premise selection in binary setting with atp feedback"
    - "reinforcement learning of theorem proving"
    - "proofwatch watchlist guidance for large theories in e"
    - "enigma efficient learning based inference guiding machine"
    - "deep network guided proof search"
    - "deepmath deep sequence models for premise selection"
    - "xgboost a scalable tree boosting system"
    - "premise selection and external provers for hol4"

Connected through hyperedge HE-2 (induced by source paper "hammering mizar by learning clause guidance"):
  with members:
    - "enigma ng efficient neural and gradient boosted inference guidance for e"
    - "reinforcement learning of theorem proving"
    - "proofwatch watchlist guidance for large theories in e"
    - "enigma efficient learning based inference guiding machine"
    - "deepmath deep sequence models for premise selection"
    - "xgboost a scalable tree boosting system"
    - "mizar 40 for mizar 40"
    - "sepia search for proofs using inferred automata"

Connected through hyperedge HE-3 (induced by source paper "planning chemical syntheses with deep neural networks and symbolic ai"):
  with members:
    - "end to end differentiable proving"
    - "modelling chemical reasoning to predict and invent reactions"
    - "retrosynthetic reaction prediction using neural sequence to sequence models"
    - "generating focussed molecule libraries for drug discovery with recurrent neural networks"
    - "building machines that learn and think like people"
    - "theano a python framework for fast computation of mathematical expressions"
    - "fast and accurate deep network learning by exponential linear units elus"
    - "training very deep networks"

Connected through hyperedge HE-4 (induced by source paper "proofwatch watchlist guidance for large theories in e"):
  with members:
    - "mastering chess and shogi by self play with a general reinforcement learning algorithm"
    - "enigma efficient learning based inference guiding machine"
    - "deep network guided proof search"
    - "tactictoe learning to reason with hol4 tactics"
    - "deepmath deep sequence models for premise selection"
    - "extending e prover with similarity based clause selection strategies"
    - "mizar 40 for mizar 40"
    - "sepia search for proofs using inferred automata"

Question: Please tell me which class the center node 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)