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 all switches strategy improvement"):
  Abstract: Strategy improvement is a widely-used and well-studied class of algorithms for solving graph-based infinite games. These algorithms are parameterized by a switching rule, and one of the most natural rules is "all switches" which switches as many edges as possible in each iteration. Continuing a recent line of work, we study all-switches strategy improvement from the perspective of computational complexity. We consider two natural decision problems, both of which have as input a game $G$, a starting strategy $s$, and an edge $e$. The problems are: 1.) The edge switch problem, namely, is the edge $e$ ever switched by all-switches strategy improvement when it is started from $s$ on game $G$? 2.) The optimal strategy problem, namely, is the edge $e$ used in the final strategy that is found by strategy improvement when it is started from $s$ on game $G$? We show $\mathtt{PSPACE}$-completeness of the edge switch problem and optimal strategy problem for the following settings: Parity games with the discrete strategy improvement algorithm of Voge and Jurdzinski; mean-payoff games with the gain-bias algorithm [14,37]; and discounted-payoff games and simple stochastic games with their standard strategy improvement algorithms. We also show $\mathtt{PSPACE}$-completeness of an analogous problem to edge switch for the bottom-antipodal algorithm for finding the sink of an Acyclic Unique Sink Orientation on a cube.

Includes members:
  Member "on simplex pivoting rules and complexity theory":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the computational power of online gradient descent")
  Member "the complexity of the simplex method":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the complexity of value iteration")
  Member "the simplex algorithm is np mighty":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "algorithms for flows over time with scheduling costs")
  Member "an exponential lower bound for the latest deterministic strategy iteration algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a parity game tale of two counters")
  Member "non oblivious strategy improvement":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a parity game tale of two counters")
  Member "the complexity of the homotopy method equilibrium selection and lemke howson solutions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a generalized training approach for multiagent learning")
  Member "exponential lower bounds for policy iteration":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a universal attractor decomposition algorithm for parity games")
  Member "linear complementarity algorithms for infinite games":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a strongly polynomial reduction for linear programs over grids")

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.DS(Data Structures and Algorithms)