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 "closing the learning planning loop with predictive state representations"):
  Abstract: A central problem in artificial intelligence is that of planning to maximize future reward under uncertainty in a partially observable environment. In this paper we propose and demonstrate a novel algorithm which accurately learns a model of such an environment directly from sequences of action-observation pairs. We then close the loop from observations to actions by planning in the learned model and recovering a policy which is near-optimal in the original environment. Specifically, we present an efficient and statistically consistent spectral algorithm for learning the parameters of a Predictive State Representation (PSR). We demonstrate the algorithm by learning a model of a simulated high-dimensional, vision-based mobile robot planning task, and then perform approximate point-based planning in the learned PSR. Analysis of our results shows that the algorithm learns a state space which efficiently captures the essential features of the environment. This representation allows accurate prediction with a small number of parameters, and enables successful and efficient planning.

Includes members:
  Member "predictive state representations a new theory for modeling dynamical systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "discovery of useful questions as auxiliary tasks")
  Member "model based bayesian reinforcement learning in large structured domains":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "expanding the active inference landscape more intrinsic motivations in the perception action loop")
  Member "planning in pomdps using multiplicity automata":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the use of non stationary policies for stationary infinite horizon markov decision processes")
  Member "reduced rank hidden markov models":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "singular value automata and approximate minimization")
  Member "a spectral algorithm for learning hidden markov models":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "combining offline models and online monte carlo tree search for planning from scratch")
  Member "perseus randomized point based value iteration for pomdps":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "mobility and blockage aware communications in millimeter wave vehicular networks")

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.LG(Machine Learning)