human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "restricted value iteration theory and algorithms"):
  Abstract: Value iteration is a popular algorithm for finding near optimal policies for POMDPs. It is ineffcient due to the need to account for the entire belief space, which necessitates the solution of large numbers of linear programs. In this paper, we study value iteration restricted to belief subsets. We show that, together with properly chosen belief subsets, restricted value iteration yields near-optimal policies and we give a condition for determining whether a given belief subset would bring about savings in space and time. We also apply restricted value iteration to two interesting classes of POMDPs, namely informative POMDPs and near-discernible POMDPs.

Includes members:
  Member "flexible decomposition algorithms for weakly coupled markov decision problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "graying the black box understanding dqns")
  Member "structured reachability analysis for markov decision processes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "reachability and differential based heuristics for solving markov decision processes")
  Member "incremental pruning a simple fast exact method for partially observable markov decision processes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "optimizing sequential medical treatments with auto encoding heuristic search in pomdps")
  Member "policy iteration for factored mdps":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi agent thompson sampling for bandit applications with sparse neighbourhood structures")
  Member "speeding up the convergence of value iteration in partially observable markov decision processes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "artificial intelligence for low resource communities influence maximization in an uncertain world")
  Member "value function approximations for partially observable markov decision processes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "point based methods for model checking in partially observable markov decision processes")
  Member "the computational complexity of probabilistic planning":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a rate distortion framework for explaining neural network decisions")
  Member "a model approximation scheme for planning in partially observable stochastic domains":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a method for speeding up value iteration in partially observable markov decision processes")

Question: Please tell me which class the source paper 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)