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: "reinforcement learning of theorem proving"
  Abstract: We introduce a theorem proving algorithm that uses practically no domain heuristics for guiding its connection-style proof search. Instead, it runs many Monte-Carlo simulations guided by reinforcement learning from previous proof attempts. We produce several versions of the prover, parameterized by different learning and guiding algorithms. The strongest version of the system is trained on a large corpus of mathematical problems and evaluated on previously unseen problems. The trained system solves within the same number of inferences over 40% more problems than a baseline prover, which is an unusually high improvement in this hard AI domain. To our knowledge this is the first time reinforcement learning has been convincingly applied to solving general mathematical problems on a large scale.

Connected through hyperedge HE-1 (induced by source paper "an experimental study of formula embeddings for automated theorem proving in first order logic"):
  with members:
    - "proof simplification and automated theorem proving"
    - "a deep reinforcement learning based approach to learning transferable proof guidance strategies"
    - "improving graph neural network representations of logical formulae with subgraph pooling"
    - "graph representations for higher order logic and theorem proving"
    - "property invariant embedding for automated reasoning"
    - "learning to reason in large theories without imitation"
    - "how powerful are graph neural networks"
    - "neural message passing for quantum chemistry"

Connected through hyperedge HE-2 (induced by source paper "deep reinforcement learning for synthesizing functions in higher order logic"):
  with members:
    - "deepsynth program synthesis for automatic task segmentation in deep reinforcement learning"
    - "cls smt bringing together combinatory logic synthesis and satisfiability modulo theories"
    - "hammering mizar by learning clause guidance"
    - "learning to prove with tactics"
    - "enigma efficient learning based inference guiding machine"
    - "tactictoe learning to reason with hol4 tactics"
    - "easy first dependency parsing with hierarchical tree lstms"
    - "xgboost a scalable tree boosting system"

Connected through hyperedge HE-3 (induced by source paper "elementary logic in linear space"):
  with members:
    - "on learning to prove"
    - "learning a sat solver from single bit supervision"
    - "gamepad a learning environment for theorem proving"
    - "deep network guided proof search"
    - "holstep a machine learning dataset for higher order logic theorem proving"
    - "analysis of boolean functions"
    - "machine learning of coq proof guidance first experiments"
    - "probabilities on sentences in an expressive logic"

Connected through hyperedge HE-4 (induced by source paper "towards finding longer proofs"):
  with members:
    - "enigma ng efficient neural and gradient boosted inference guidance for e"
    - "the minerl competition on sample efficient reinforcement learning using human priors"
    - "meta learning of sequential strategies"
    - "grunge a grand unified atp challenge"
    - "analysing mathematical reasoning abilities of neural models"
    - "graph representations for higher order logic and theorem proving"
    - "learning to speak and act in a fantasy text adventure game"
    - "hammering mizar by learning clause guidance"

Connected through hyperedge HE-5 (induced by source paper "a survey on theorem provers in formal methods"):
  with members:
    - "comparison of two theorem provers isabelle hol and coq"
    - "the boyer moore waterfall model revisited"
    - "qwire practice formal verification of quantum circuits in coq"
    - "proofwatch watchlist guidance for large theories in e"
    - "verifying asymptotic time complexity of imperative programs in isabelle"
    - "formalized lambek calculus in higher order logic hol4"
    - "the x86isa books features usage and future plans"
    - "constraint solving for finite model finding in smt solvers"

Connected through hyperedge HE-6 (induced by source paper "learning to prove theorems via interacting with proof assistants"):
  with members:
    - "holist an environment for machine learning of higher order theorem proving"
    - "code2vec learning distributed representations of code"
    - "gamepad a learning environment for theorem proving"
    - "generative code modeling with graphs"
    - "learning to prove with tactics"
    - "end to end differentiable proving"
    - "deep network guided proof search"
    - "learning to represent programs with graphs"

Connected through hyperedge HE-7 (induced by source paper "a deep reinforcement learning based approach to learning transferable proof guidance strategies"):
  with members:
    - "enigma ng efficient neural and gradient boosted inference guidance for e"
    - "towards finding longer proofs"
    - "guiding theorem proving by recurrent neural networks"
    - "graph representations for higher order logic and theorem proving"
    - "hammering mizar by learning clause guidance"
    - "property invariant embedding for automated reasoning"
    - "learning to reason in large theories without imitation"
    - "learning heuristics for automated reasoning through deep reinforcement learning"

Connected through hyperedge HE-8 (induced by source paper "holist an environment for machine learning of higher order theorem proving"):
  with members:
    - "gamepad a learning environment for theorem proving"
    - "deep network guided proof search"
    - "holstep a machine learning dataset for higher order logic theorem proving"
    - "tactictoe learning to reason with hol4 tactics"
    - "premise selection for theorem proving by deep graph embedding"
    - "squad 100 000 questions for machine comprehension of text"
    - "wavenet a generative model for raw audio"
    - "holophrasm a neural automated theorem prover for higher order logic"

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.AI(Artificial Intelligence)