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 "finite memory strategy synthesis for robust multidimensional mean payoff objectives"):
  Abstract: Two-player games on graphs provide the mathematical foundation for the study of reactive systems. In the quantitative framework, an objective assigns a value to every play, and the goal of player 1 is to minimize the value of the objective. In this framework, there are two relevant synthesis problems to consider: the quantitative analysis problem is to compute the minimal (or infimum) value that player 1 can assure, and the boolean analysis problem asks whether player 1 can assure that the value of the objective is at most $\nu$ (for a given threshold $\nu$). Mean-payoff expression games are played on a multidimensional weighted graph. An atomic mean-payoff expression objective is the mean-payoff value (the long-run average weight) of a certain dimension, and the class of mean-payoff expressions is the closure of atomic mean-payoff expressions under the algebraic operations of $\MAX,\MIN$, numerical complement and $\SUM$. In this work, we study for the first time the strategy synthesis problems for games with robust quantitative objectives, namely, games with mean-payoff expression objectives. While in general, optimal strategies for these games require infinite-memory, in synthesis we are typically interested in the construction of a finite-state system. Hence, we consider games in which player 1 is restricted to finite-memory strategies, and our main contribution is as follows. We prove that for mean-payoff expressions, the quantitative analysis problem is computable, and the boolean analysis problem is inter-reducible with Hilbert's tenth problem over rationals --- a fundamental long-standing open problem in computer science and mathematics.

Includes members:
  Member "efficient controller synthesis for consumption games with multiple resource types":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "energy mean payoff games")
  Member "strategy synthesis for multi dimensional quantitative objectives":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "games where you can play optimally with finite memory")
  Member "the complexity of mean payoff automaton expression":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "decidable weighted expressions with presburger combinators")
  Member "generalized mean payoff and energy games":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "deciding fast termination for probabilistic vass with nondeterminism")
  Member "expressiveness and closure properties for quantitative languages":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "weighted pcl over product valuation monoids")
  Member "mean payoff automaton expressions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (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.LO(Logic in Computer Science)