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: "path planning under time dependent uncertainty"
  Abstract: Standard algorithms for finding the shortest path in a graph require that the cost of a path be additive in edge costs, and typically assume that costs are deterministic. We consider the problem of uncertain edge costs, with potential probabilistic dependencies among the costs. Although these dependencies violate the standard dynamic-programming decomposition, we identify a weaker stochastic consistency condition that justifies a generalized dynamic-programming approach based on stochastic dominance. We present a revised path-planning algorithm and prove that it produces optimal paths under time-dependent uncertain costs. We test the algorithm by applying it to a model of stochastic bus networks, and present empirical performance results comparing it to some alternatives. Finally, we consider extensions of these concepts to a more general class of problems of heuristic search under uncertainty.

Connected through hyperedge HE-1 (induced by source paper "using qualitative relationships for bounding probability distributions"):
  with members:
    - "bounded conditioning flexible inference for decisions under scarce resources"
    - "incremental tradeoff resolution in qualitative probabilistic networks"
    - "robustness analysis of bayesian networks with local convex sets of distributions"
    - "computing upper and lower bounds on likelihoods in intractable networks"
    - "state space abstraction for anytime evaluation of probabilistic networks"
    - "localized partial evaluation of belief networks"
    - "propagation of 2 monotone lower probabilities on an undirected graph"
    - "incremental probabilistic inference"

Connected through hyperedge HE-2 (induced by source paper "robust belief roadmap planning under intermittent sensing"):
  with members:
    - "sampling based algorithms for optimal motion planning"

Connected through hyperedge HE-3 (induced by source paper "search for choquet optimal paths under uncertainty"):
  with members:
    - "optimal factory scheduling using stochastic dominance a"
    - "a constraint satisfaction approach to the robust spanning tree problem with interval data"
    - "an axiomatic approach to robustness in search problems with multiple scenarios"

Connected through hyperedge HE-4 (induced by source paper "an axiomatic approach to robustness in search problems with multiple scenarios"):
  with members:
    - "optimal factory scheduling using stochastic dominance a"
    - "a constraint satisfaction approach to the robust spanning tree problem with interval data"

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.AI(Artificial Intelligence)