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: "unifying two views on multiple mean payoff objectives in markov decision processes"
  Abstract: We consider Markov decision processes (MDPs) with multiple limit-average (or mean-payoff) objectives. There exist two different views: (i) the expectation semantics, where the goal is to optimize the expected mean-payoff objective, and (ii) the satisfaction semantics, where the goal is to maximize the probability of runs such that the mean-payoff value stays above a given vector. We consider optimization with respect to both objectives at once, thus unifying the existing semantics. Precisely, the goal is to optimize the expectation while ensuring the satisfaction constraint. Our problem captures the notion of optimization with respect to strategies that are risk-averse (i.e., ensure certain probabilistic guarantee). Our main results are as follows: First, we present algorithms for the decision problems which are always polynomial in the size of the MDP. We also show that an approximation of the Pareto-curve can be computed in time polynomial in the size of the MDP, and the approximation factor, but exponential in the number of dimensions. Second, we present a complete characterization of the strategy complexity (in terms of memory bounds and randomization) required to solve our problem.

Connected through hyperedge HE-1 (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"
    - "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"
    - "the odds of staying on budget"

Connected through hyperedge HE-2 (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"
    - "knowledge spaces and the completeness of learning strategies"
    - "the complexity of ergodic mean payoff games"
    - "verification of markov decision processes using learning algorithms"
    - "markov decision processes with multiple long run averageobjectives"
    - "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-3 (induced by source paper "optimizing the expected mean payoff in energy markov decision processes"):
  with members:
    - "an omega algebra for real time energy problems"
    - "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"
    - "the odds of staying on budget"
    - "polynomial time algorithms for energy games with special weight structures"
    - "solving parity games on integer vectors"

Connected through hyperedge HE-4 (induced by source paper "perfect information stochastic games with generalized mean payoff objectives"):
  with members:
    - "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"
    - "markov decision processes with multiple long run averageobjectives"
    - "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-5 (induced by source paper "efficient quantile computation in markov chains via counting problems for parikh images"):
  with members:
    - "complexity of problems of commutative grammars"
    - "counting euler tours in undirected bounded treewidth graphs"
    - "multidimensional beyond worst case and almost sure problems for mean payoff objectives"
    - "the complexity of the kth largest subset problem and related problems"
    - "variations on the stochastic shortest path problem"
    - "the odds of staying on budget"
    - "percentile queries in multi dimensional markov decision processes"
    - "computing quantiles in markov reward models"

Connected through hyperedge HE-6 (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"
    - "nested weighted automata"
    - "markov decision processes with multiple long run averageobjectives"
    - "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-7 (induced by source paper "minimizing expected cost under hard boolean constraints with applications to quantitative synthesis"):
  with members:
    - "multidimensional beyond worst case and almost sure problems for mean payoff objectives"
    - "meet your expectations with guarantees beyond worst case synthesis in quantitative games"

Connected through hyperedge HE-8 (induced by source paper "multidimensional beyond worst case and almost sure problems for mean payoff objectives"):
  with members:
    - "percentile queries in multi dimensional markov decision processes"
    - "markov decision processes with multiple long run averageobjectives"
    - "meet your expectations with guarantees beyond worst case synthesis in quantitative games"
    - "the complexity of multi mean payoff and multi energy games"
    - "hyperplane separation technique for multidimensional mean payoff games"

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.LO(Logic in Computer Science)