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 "pebble games proof complexity and time space trade offs"):
  Abstract: Pebble games were extensively studied in the 1970s and 1980s in a number of different contexts. The last decade has seen a revival of interest in pebble games coming from the field of proof complexity. Pebbling has proven to be a useful tool for studying resolution-based proof systems when comparing the strength of different subsystems, showing bounds on proof space, and establishing size-space trade-offs. This is a survey of research in proof complexity drawing on results and tools from pebbling, with a focus on proof space lower bounds and trade-offs between proof size and proof space.

Includes members:
  Member "clause learning algorithms with many restarts and bounded width resolution":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "towards a complexity theoretic understanding of restarts in sat solvers")
  Member "understanding space in proof complexity separations and trade offs via substitutions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "near optimal lower bounds on quantifier depth and weisfeiler leman refinement steps")
  Member "on the relative strength of pebbling and resolution":
    also connected through other hyperedges:
      (none)
  Member "towards an optimal separation of space and length in resolution":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the complexity of finding narrow proofs")
  Member "towards understanding and harnessing the potential of clause learning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on cdcl based proof systems with the ordered decision strategy")

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.CC(Computational Complexity)