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: "heuristic search value iteration for pomdps"
  Abstract: We present a novel POMDP planning algorithm called heuristic search value iteration (HSVI).HSVI is an anytime algorithm that returns a policy and a provable bound on its regret with respect to the optimal policy. HSVI gets its power by combining two well-known techniques: attention-focusing search heuristics and piecewise linear convex representations of the value function. HSVI's soundness and convergence have been proven. On some benchmark problems from the literature, HSVI displays speedups of greater than 100 with respect to other state-of-the-art POMDP value iteration algorithms. We also apply HSVI to a new rover exploration problem 10 times larger than most POMDP problems in the literature.

Connected through hyperedge HE-1 (induced by source paper "point based methods for model checking in partially observable markov decision processes"):
  with members:
    - "verification of uncertain pomdps using barrier certificates"
    - "bounded policy synthesis for pomdps with safe reachability objectives"
    - "a storm is coming a modern probabilistic model checker"
    - "inverse reward design"
    - "qualitative analysis of pomdps with temporal logic specifications for robotics applications"
    - "a learning based approach to control synthesis of markov decision processes for linear temporal logic specifications"
    - "what is decidable about partially observable markov decision processes with omega regular objectives"
    - "a theory of goal oriented mdps with dead ends"

Connected through hyperedge HE-2 (induced by source paper "reinforcement learning of risk constrained policies in markov decision processes"):
  with members:
    - "expectation optimization with probabilistic guarantees in pomdps with discounted sum objectives"
    - "vulcan a monte carlo algorithm for large chance constrained mdps with risk bounding functions"
    - "variations on the stochastic shortest path problem"
    - "meet your expectations with guarantees beyond worst case synthesis in quantitative games"
    - "reinforcement learning a survey"

Connected through hyperedge HE-3 (induced by source paper "optimizing sequential medical treatments with auto encoding heuristic search in pomdps"):
  with members:
    - "impala scalable distributed deep rl with importance weighted actor learner architectures"
    - "representation balancing mdps for off policy policy evaluation"
    - "distributed prioritized experience replay"
    - "deep variational reinforcement learning for pomdps"
    - "learning longer term dependencies in rnns with auxiliary losses"
    - "distributed distributional deterministic policy gradients"
    - "janossy pooling learning deep permutation invariant functions for variable size inputs"
    - "filtering variational objectives"

Connected through hyperedge HE-4 (induced by source paper "combining offline models and online monte carlo tree search for planning from scratch"):
  with members:
    - "bayesian reinforcement learning in factored pomdps"
    - "learning in pomdps with monte carlo tree search"
    - "despot online pomdp planning with regularization"
    - "bayesian reinforcement learning a survey"
    - "efficient learning and planning with compressed predictive states"
    - "predictive state representations a new theory for modeling dynamical systems"
    - "learning to make predictions in partially observable environments without a generative model"
    - "closing the learning planning loop with predictive state representations"

Connected through hyperedge HE-5 (induced by source paper "control theory meets pomdps a hybrid systems approach"):
  with members:
    - "safe policy synthesis in multi agent pomdps via discrete time barrier functions"
    - "verification of uncertain pomdps using barrier certificates"
    - "understanding the role of adaptivity in machine teaching the case of version space learners"
    - "barrier certificates for assured machine teaching"
    - "privacy verification in pomdps via barrier certificates"
    - "machine teaching a new paradigm for building machine learning systems"
    - "safe learning of regions of attraction for uncertain nonlinear systems with gaussian processes"
    - "control of probabilistic systems under dynamic partially known environments with temporal logic specifications"

Connected through hyperedge HE-6 (induced by source paper "a deep actor critic reinforcement learning framework for dynamic multichannel access"):
  with members:
    - "reinforcement learning based resource allocation in fog radio access networks for various iot environments"
    - "applications of deep reinforcement learning in communications and networking a survey"
    - "deep reinforcement learning for dynamic multichannel access in wireless networks"
    - "deep learning in mobile and wireless networking a survey"
    - "deep reinforcement learning for resource allocation in v2v communications"
    - "deep multi user reinforcement learning for distributed dynamic spectrum access"
    - "deep reinforcement learning multiple access for heterogeneous wireless networks"
    - "maa a heuristic search algorithm for solving decentralized pomdps"

Connected through hyperedge HE-7 (induced by source paper "online learning and planning in partially observable domains without prior knowledge"):
  with members:
    - "combining offline models and online monte carlo tree search for planning from scratch"
    - "bayesian reinforcement learning in factored pomdps"
    - "learning in pomdps with monte carlo tree search"
    - "bayesian reinforcement learning a survey"
    - "efficient learning and planning with compressed predictive states"
    - "predictive state representations a new theory for modeling dynamical systems"
    - "online planning algorithms for pomdps"
    - "a spectral algorithm for learning hidden markov models"

Connected through hyperedge HE-8 (induced by source paper "memory bounded open loop planning in large pomdps using thompson sampling"):
  with members:
    - "leveraging statistical multi agent online planning with emergent value function approximation"
    - "open loop execution of tree search algorithms"
    - "stacked thompson bandits"
    - "further optimal regret bounds for thompson sampling"
    - "compiling uncertainty away in conformant planning problems with bounded width"
    - "online planning algorithms for pomdps"

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)