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 "a deep reinforcement learning based approach to learning transferable proof guidance strategies"):
  Abstract: Traditional first-order logic (FOL) reasoning systems usually rely on manual heuristics for proof guidance. We propose TRAIL: a system that learns to perform proof guidance using reinforcement learning. A key design principle of our system is that it is general enough to allow transfer to problems in different domains that do not share the same vocabulary of the training set. To do so, we developed a novel representation of the internal state of a prover in terms of clauses and inference actions. We also propose a novel neural-based attention mechanism to learn interactions between clauses. We demonstrate that this approach enables the system to generalize from training to test data across domains with different vocabularies, suggesting that the neural architecture in TRAIL is well suited for representing and processing of logical formalisms. We also show that TRAIL's learned strategies provide a comparable performance to an established heuristics-based theorem prover.

Includes members:
  Member "enigma ng efficient neural and gradient boosted inference guidance for e":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "towards finding longer proofs")
  Member "towards finding longer proofs":
    also connected through other hyperedges:
      (none)
  Member "guiding theorem proving by recurrent neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "exploration of neural machine translation in autoformalization of mathematics in mizar")
  Member "graph representations for higher order logic and theorem proving":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "teaching temporal logics to neural networks")
  Member "hammering mizar by learning clause guidance":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "deep reinforcement learning for synthesizing functions in higher order logic")
  Member "property invariant embedding for automated reasoning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "an experimental study of formula embeddings for automated theorem proving in first order logic")
  Member "learning to reason in large theories without imitation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "an experimental study of formula embeddings for automated theorem proving in first order logic")
  Member "learning heuristics for automated reasoning through deep reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "graph representations for higher order logic and theorem proving")

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.AI(Artificial Intelligence)