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 "the complexity of multi mean payoff and multi energy games"):
  Abstract: In mean-payoff games, the objective of the protagonist is to ensure that the limit average of an infinite sequence of numeric weights is nonnegative. In energy games, the objective is to ensure that the running sum of weights is always nonnegative. Multi-mean-payoff and multi-energy games replace individual weights by tuples, and the limit average (resp. running sum) of each coordinate must be (resp. remain) nonnegative. These games have applications in the synthesis of resource-bounded processes with multiple resources. #R##N#We prove the finite-memory determinacy of multi-energy games and show the inter-reducibility of multimean-payoff and multi-energy games for finite-memory strategies. We also improve the computational complexity for solving both classes of games with finite-memory strategies: while the previously best known upper bound was EXPSPACE, and no lower bound was known, we give an optimal coNP-complete bound. For memoryless strategies, we show that the problem of deciding the existence of a winning strategy for the protagonist is NP-complete. Finally we present the first solution of multi-meanpayoff games with infinite-memory strategies. We show that multi-mean-payoff games with mean-payoff-sup objectives can be decided in NP and coNP, whereas multi-mean-payoff games with mean-payoff-inf objectives are coNP-complete.

Includes members:
  Member "a framework for automated competitive analysis of on line scheduling of firm deadline tasks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "perfect information stochastic games with generalized mean payoff objectives")
  Member "polynomial time algorithms for energy games with special weight structures":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "optimizing the expected mean payoff in energy markov decision processes")
  Member "looking at mean payoff and total payoff through windows":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "games where you can play optimally with finite memory")
  Member "efficient controller synthesis for consumption games with multiple resource types":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "energy mean payoff games")
  Member "strategy synthesis for multi dimensional quantitative objectives":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "games where you can play optimally with finite memory")
  Member "hyperplane separation technique for multidimensional mean payoff games":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "deciding fast termination for probabilistic vass with nondeterminism")
  Member "reachability games on extended vector addition systems with states":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "energy mean payoff games")
  Member "mean payoff automaton expressions":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "decidable weighted expressions with presburger combinators")

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.GT(Computer Science and Game Theory)