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: "scaling up decentralized mdps through heuristic search"
  Abstract: Decentralized partially observable Markov decision processes (Dec-POMDPs) are rich models for cooperative decision-making under uncertainty, but are often intractable to solve optimally (NEXP-complete). The transition and observation independent Dec-MDP is a general subclass that has been shown to have complexity in NP, but optimal algorithms for this subclass are still inefficient in practice. In this paper, we first provide an updated proof that an optimal policy does not depend on the histories of the agents, but only the local observations. We then present a new algorithm based on heuristic search that is able to expand search nodes by using constraint optimization. We show experimental results comparing our approach with the state-of-the-art DecMDP and Dec-POMDP solvers. These results show a reduction in computation time and an increase in scalability by multiple orders of magnitude in a number of benchmarks.

Connected through hyperedge HE-1 (induced by source paper "a decentralized optimization framework for energy harvesting devices"):
  with members:
    - "battery powered devices in wpcns"
    - "decentralized transmission policies for energy harvesting devices"
    - "optimal adaptive random multiaccess in energy harvesting wireless sensor networks"
    - "energy harvesting wireless communications a review of recent advances"
    - "markov decision processes with applications in wireless sensor networks a survey"
    - "joint transmission and energy transfer policies for energy harvesting devices with finite batteries"
    - "universally near optimal online power control for energy harvesting nodes"
    - "wireless networks with rf energy harvesting a contemporary survey"

Connected through hyperedge HE-2 (induced by source paper "decentralized transmission policies for energy harvesting devices"):
  with members:
    - "a decentralized optimization framework for energy harvesting devices"
    - "optimal adaptive random multiaccess in energy harvesting wireless sensor networks"
    - "energy harvesting wireless communications a review of recent advances"
    - "joint transmission and energy transfer policies for energy harvesting devices with finite batteries"
    - "a learning theoretic approach to energy harvesting communication system optimization"
    - "optimum transmission policies for battery limited energy harvesting nodes"
    - "optimal energy management policies for energy harvesting sensor nodes"

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)