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 "partial observation stochastic games how to win when belief fails"):
  Abstract: In two-player finite-state stochastic games of partial observation on graphs, in every state of the graph, the players simultaneously choose an action, and their joint actions determine a probability distribution over the successor states. We consider reachability objectives where player 1 tries to ensure a target state to be visited almost-surely or positively. On the basis of information, the game can be one-sided with either (a)player 1 or (b)player 2 having partial observation, or two-sided with both players having partial observation. On the basis of randomization (a)players may not be allowed to use randomization (pure strategies), or (b)may choose a probability distribution over actions but the actual random choice is not visible (actions invisible), or (c)may use full randomization. Our results for pure strategies are as follows: (1)For one-sided games with player 2 perfect observation we show that belief-based strategies are not sufficient, and present an exponential upper bound on memory both for almost-sure and positive winning strategies; we show that the problem of deciding the existence of almost-sure and positive winning strategies for player 1 is EXPTIME-complete and present symbolic algorithms that avoid the explicit exponential construction. (2)For one-sided games with player 1 perfect observation we show that non-elementary memory is both necessary and sufficient for both almost-sure and positive winning strategies. (3)We show that for the two-sided case finite memory strategies are sufficient for both positive and almost-sure winning. We establish the equivalence of the almost-sure winning problem for pure strategies with randomized strategies with actions invisible. Our equivalence result exhibit serious flaws in previous results in the literature: we show a non-elementary memory lower bound for almost-sure winning whereas an exponential upper bound was claimed.

Includes members:
  Member "the complexity of partial observation stochastic parity games with finite memory strategies":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "secure control under partial observability with temporal logic constraints")
  Member "what is decidable about partially observable markov decision processes with omega regular objectives":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "point based methods for model checking in partially observable markov decision processes")
  Member "forward analysis for wsts part ii complete wsts":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the ideal approach to computing closed subsets in well quasi orderings")
  Member "decidable problems for probabilistic automata on infinite words":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the complexity of pomdps with long run average objectives")
  Member "power of randomization in automata on infinite strings":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the complexity of pomdps with long run average objectives")
  Member "reachability games on extended vector addition systems with states":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "energy mean payoff games")
  Member "randomness for free":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "parameter independent strategies for pmdps via pomdps")
  Member "qualitative analysis of partially observable markov decision processes":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "stochastic finite state control of pomdps with ltl specifications")

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)