human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "the odds of staying on budget"
  Abstract: Given Markov chains and Markov decision processes (MDPs) whose transitions are labelled with non-negative integer costs, we study the computational complexity of deciding whether the probability of paths whose accumulated cost satisfies a Boolean combination of inequalities exceeds a given threshold. For acyclic Markov chains, we show that this problem is PP-complete, whereas it is hard for the PosSLP problem and in PSPACE for general Markov chains. Moreover, for acyclic and general MDPs, we prove PSPACE- and EXP-completeness, respectively. Our results have direct implications on the complexity of computing reward quantiles in succinctly represented stochastic systems.

Connected through hyperedge HE-1 (induced by source paper "life is random time is not markov decision processes with window objectives"):
  with members:
    - "multi weighted markov decision processes with reachability objectives"
    - "expected window mean payoff"
    - "universal trees grow inside separating automata quasi polynomial lower bounds for parity games"
    - "the complexity of mean payoff games using universal graphs"
    - "extending finite memory determinacy by boolean combination of winning conditions"
    - "value iteration for long run average reward in markov decision processes"
    - "threshold constraints with guarantees for parity objectives in markov decision processes"
    - "a storm is coming a modern probabilistic model checker"

Connected through hyperedge HE-2 (induced by source paper "multi weighted markov decision processes with reachability objectives"):
  with members:
    - "stochastic shortest paths and weight bounded properties in markov decision processes"
    - "stream differential equations specification formats and solution methods"
    - "threshold constraints with guarantees for parity objectives in markov decision processes"
    - "maximizing the conditional expected reward for reaching the goal"
    - "unifying two views on multiple mean payoff objectives in markov decision processes"
    - "multidimensional beyond worst case and almost sure problems for mean payoff objectives"
    - "knowledge spaces and the completeness of learning strategies"
    - "variations on the stochastic shortest path problem"

Connected through hyperedge HE-3 (induced by source paper "conditional value at risk for reachability and mean payoff in markov decision processes"):
  with members:
    - "quantile markov decision process"
    - "value iteration for long run average reward in markov decision processes"
    - "maximizing the conditional expected reward for reaching the goal"
    - "multidimensional beyond worst case and almost sure problems for mean payoff objectives"
    - "percentile queries in multi dimensional markov decision processes"
    - "trading performance for stability in markov decision processes"
    - "computing quantiles in markov reward models"
    - "meet your expectations with guarantees beyond worst case synthesis in quantitative games"

Connected through hyperedge HE-4 (induced by source paper "stochastic shortest paths and weight bounded properties in markov decision processes"):
  with members:
    - "mdps with energy parity objectives"
    - "optimizing the expected mean payoff in energy markov decision processes"
    - "qualitative analysis of vass induced mdps"
    - "variations on the stochastic shortest path problem"
    - "computing quantiles in markov reward models"
    - "meet your expectations with guarantees beyond worst case synthesis in quantitative games"
    - "energy and mean payoff parity markov decision processes"
    - "energy parity games"

Connected through hyperedge HE-5 (induced by source paper "infinite duration bidding games"):
  with members:
    - "determinacy in discrete bidding infinite duration games"
    - "infinite duration poorman bidding games"
    - "how much lookahead is needed to win infinite games"
    - "discrete all pay bidding games"
    - "non zero sum games for reactive synthesis"
    - "pure nash equilibria in concurrent deterministic games"
    - "variations on the stochastic shortest path problem"
    - "secure equilibria in weighted games"

Connected through hyperedge HE-6 (induced by source paper "maximizing the conditional expected reward for reaching the goal"):
  with members:
    - "termination analysis of probabilistic programs through positivstellensatz s"
    - "synthesizing probabilistic invariants via doob s decomposition"
    - "variations on the stochastic shortest path problem"
    - "markov decision processes with multiple long run averageobjectives"
    - "quantitative analysis of information leakage in probabilistic and nondeterministic systems"
    - "decisive markov chains"

Connected through hyperedge HE-7 (induced by source paper "optimizing the expected mean payoff in energy markov decision processes"):
  with members:
    - "an omega algebra for real time energy problems"
    - "unifying two views on multiple mean payoff objectives in markov decision processes"
    - "qualitative analysis of vass induced mdps"
    - "average energy games"
    - "multidimensional beyond worst case and almost sure problems for mean payoff objectives"
    - "zero reachability in probabilistic multi counter automata"
    - "polynomial time algorithms for energy games with special weight structures"
    - "solving parity games on integer vectors"

Connected through hyperedge HE-8 (induced by source paper "reconciling rationality and stochasticity rich behavioral models in two player games"):
  with members:
    - "average energy games"
    - "non zero sum games for reactive synthesis"
    - "variations on the stochastic shortest path problem"
    - "percentile queries in multi dimensional markov decision processes"
    - "expectations or guarantees i want it all a crossroad between games and mdps"
    - "computing quantiles in markov reward models"
    - "meet your expectations with guarantees beyond worst case synthesis in quantitative games"
    - "strategy synthesis for multi dimensional quantitative objectives"

Question: Please tell me which class the center node 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)