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 "on the linear belief compression of pomdps a re examination of current methods"):
  Abstract: Belief compression improves the tractability of large-scale partially observable Markov decision processes (POMDPs) by finding projections from high-dimensional belief space onto low-dimensional approximations, where solving to obtain action selection policies requires fewer computations. This paper develops a unified theoretical framework to analyse three existing linear belief compression approaches, including value-directed compression and two non-negative matrix factorisation (NMF) based algorithms. The results indicate that all the three known belief compression methods have their own critical deficiencies. Therefore, projective NMF belief compression is proposed (P-NMF), aiming to overcome the drawbacks of the existing techniques. The performance of the proposed algorithm is examined on four POMDP problems of reasonably large scale, in comparison with existing techniques. Additionally, the competitiveness of belief compression is compared empirically to a state-of-the-art heuristic search based POMDP solver and their relative merits in solving large-scale POMDPs are investigated.

Includes members:
  Member "value directed belief state approximation for pomdps":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "exploiting causality for selective belief filtering in dynamic bayesian networks")
  Member "point based pomdp algorithms improved analysis and implementation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "optimizing sequential medical treatments with auto encoding heuristic search in pomdps")
  Member "heuristic search value iteration for pomdps":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "point based methods for model checking in partially observable markov decision processes")
  Member "perseus randomized point based value iteration for pomdps":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "mobility and blockage aware communications in millimeter wave vehicular networks")
  Member "restricted value iteration theory and algorithms":
    also connected through other hyperedges:
      (none)
  Member "value function approximations for partially observable markov decision processes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "point based methods for model checking 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)