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: "markov decision processes with multiple long run averageobjectives"
  Abstract: We study Markov decision processes (MDPs) with multiple#N#limit-average (or mean-payoff) functions. We consider two#N#different objectives, namely, expectation and satisfaction#N#objectives. Given an MDP with k limit-average functions, in the#N#expectation objective the goal is to maximize the expected#N#limit-average value, and in the satisfaction objective the goal#N#is to maximize the probability of runs such that the#N#limit-average value stays above a given vector. We show that#N#under the expectation objective, in contrast to the case of one#N#limit-average function, both randomization and memory are#N#necessary for strategies even for epsilon-approximation, and#N#that finite-memory randomized strategies are sufficient for#N#achieving Pareto optimal values. Under the satisfaction#N#objective, in contrast to the case of one limit-average#N#function, infinite memory is necessary for strategies achieving#N#a specific value (i.e. randomized finite-memory strategies are#N#not sufficient), whereas memoryless randomized strategies are#N#sufficient for epsilon-approximation, for all epsilon>0. We#N#further prove that the decision problems for both expectation#N#and satisfaction objectives can be solved in polynomial time#N#and the trade-off curve (Pareto curve) can be#N#epsilon-approximated in time polynomial in the size of the MDP#N#and 1/epsilon, and exponential in the number of limit-average#N#functions, for all epsilon>0. Our analysis also reveals flaws#N#in previous work for MDPs with multiple mean-payoff functions#N#under the expectation objective, corrects the flaws, and allows#N#us to obtain improved results.

Connected through hyperedge HE-1 (induced by source paper "deciding fast termination for probabilistic vass with nondeterminism"):
  with members:
    - "reachability in vector addition systems is primitive recursive in fixed dimension"
    - "the reachability problem for petri nets is not elementary"
    - "efficient algorithms for asymptotic bounds on termination time in vass"
    - "perfect half space games"
    - "automated recurrence analysis for almost linear expected runtime bounds"
    - "bounded expectations resource analysis for probabilistic programs"
    - "non polynomial worst case analysis of recursive programs"
    - "complexity hierarchies beyond elementary"

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 "markov automata with multiple objectives"):
  with members:
    - "a storm is coming a modern probabilistic model checker"
    - "safety constrained reinforcement learning for mdps"
    - "variations on the stochastic shortest path problem"
    - "analysis of timed and long run objectives for markov automata"
    - "a survey of multi objective sequential decision making"
    - "trading performance for stability in markov decision processes"
    - "meet your expectations with guarantees beyond worst case synthesis in quantitative games"
    - "pareto curves for probabilistic model checking"

Connected through hyperedge HE-4 (induced by source paper "value iteration for long run average reward in markov decision processes"):
  with members:
    - "multigain a controller synthesis tool for mdps with multiple mean payoff objectives"
    - "unifying two views on multiple mean payoff objectives in markov decision processes"
    - "knowledge spaces and the completeness of learning strategies"
    - "the complexity of ergodic mean payoff games"
    - "verification of markov decision processes using learning algorithms"
    - "faster algorithms for markov decision processes with low treewidth"
    - "trading performance for stability in markov decision processes"
    - "assume guarantee abstraction refinement for probabilistic systems"

Connected through hyperedge HE-5 (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"
    - "the odds of staying on budget"
    - "quantitative analysis of information leakage in probabilistic and nondeterministic systems"
    - "decisive markov chains"

Connected through hyperedge HE-6 (induced by source paper "perfect information stochastic games with generalized mean payoff objectives"):
  with members:
    - "unifying two views on multiple mean payoff objectives in markov decision processes"
    - "multidimensional beyond worst case and almost sure problems for mean payoff objectives"
    - "fixed dimensional energy games are in pseudo polynomial time"
    - "two player perfect information shift invariant submixing stochastic games are half positional"
    - "a framework for automated competitive analysis of on line scheduling of firm deadline tasks"
    - "synthesis from ltl specifications with mean payoff objectives"
    - "the complexity of multi mean payoff and multi energy games"
    - "finite memory strategy synthesis for robust multidimensional mean payoff objectives"

Connected through hyperedge HE-7 (induced by source paper "quantitative automata under probabilistic semantics"):
  with members:
    - "nested weighted limit average automata of bounded width"
    - "multigain a controller synthesis tool for mdps with multiple mean payoff objectives"
    - "unifying two views on multiple mean payoff objectives in markov decision processes"
    - "nested weighted automata"
    - "discounting in ltl"
    - "energy and mean payoff parity markov decision processes"
    - "measuring and synthesizing systems in probabilistic environments"
    - "expressiveness and closure properties for quantitative languages"

Connected through hyperedge HE-8 (induced by source paper "transition based versus state based reward functions for mdps with value at risk"):
  with members:
    - "percentile queries in multi dimensional markov decision processes"
    - "a survey of multi objective sequential decision making"
    - "topological value iteration algorithms"
    - "mean variance optimization in markov decision processes"

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.GT(Computer Science and Game Theory)