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: "optimality of myopic sensing in multi channel opportunistic access"
  Abstract: We consider opportunistic communications over multiple channels where the state ("good" or "bad") of each channel evolves as independent and identically distributed Markov processes. A user, with limited sensing and access capability, chooses one channel to sense and subsequently access (based on the sensed channel state) in each time slot. A reward is obtained when the user senses and accesses a "good" channel. The objective is to design the optimal channel selection policy that maximizes the expected reward accrued over time. This problem can be generally cast as a Partially Observable Markov Decision Process (POMDP) or a restless multi-armed bandit process, to which optimal solutions are often intractable. We show in this paper that the myopic policy, with a simple and robust structure, achieves optimality under certain conditions. This result finds applications in opportunistic communications in fading environment, cognitive radio networks for spectrum overlay, and resource-constrained jamming and anti-jamming.

Connected through hyperedge HE-1 (induced by source paper "thompson sampling in non episodic restless bandits"):
  with members:
    - "regret bounds for thompson sampling in restless bandit problems"
    - "learning unknown markov decision processes a thompson sampling approach"
    - "learning to optimize via posterior sampling"
    - "regret bounds for restless markov bandits"

Connected through hyperedge HE-2 (induced by source paper "cost aware learning and optimization for opportunistic spectrum access"):
  with members:
    - "an online approach to dynamic channel access and transmission scheduling"
    - "cascading bandits learning to rank in the cascade model"
    - "further optimal regret bounds for thompson sampling"
    - "analysis of thompson sampling for the multi armed bandit problem"
    - "multi channel opportunistic access a case of restless bandits with multiple plays"
    - "on myopic sensing for multi channel opportunistic access structure optimality and performance"
    - "joint design and separation principle for opportunistic spectrum access in the presence of sensing errors"
    - "cognitive medium access exploration exploitation and competition"

Connected through hyperedge HE-3 (induced by source paper "sequential decision making with limited observation capability application to wireless networks"):
  with members:
    - "a hidden markov restless multi armed bandit model for playout recommendation systems"
    - "opportunistic scheduling as restless bandits"
    - "multiuser scheduling in a markov modeled downlink using randomly delayed arq feedback"
    - "asymptotically optimal downlink scheduling over markovian fading channels"
    - "downlink scheduling over markovian fading channels"
    - "on myopic sensing for multi channel opportunistic access structure optimality and performance"

Connected through hyperedge HE-4 (induced by source paper "low complexity optimal scheduling over time correlated fading channels with arq feedback"):
  with members:
    - "green communication via power optimized harq protocols"
    - "exploiting hybrid channel information for downlink multi user mimo scheduling"
    - "multiuser scheduling in a markov modeled downlink using randomly delayed arq feedback"
    - "asymptotically optimal downlink scheduling over markovian fading channels"
    - "joint scheduling and resource allocation in the ofdma downlink utility maximization under imperfect channel state information"
    - "scheduling with rate adaptation under incomplete knowledge of channel estimator statistics"
    - "exploiting channel memory for joint estimation and scheduling in downlink networks"

Connected through hyperedge HE-5 (induced by source paper "power aware wireless file downloading a lyapunov indexing approach to a constrained restless bandit problem"):
  with members:
    - "power aware wireless file downloading a constrained restless bandit approach"
    - "exploiting channel memory for joint estimation and scheduling in downlink networks"
    - "throughput optimal opportunistic scheduling in the presence of flow level dynamics"

Connected through hyperedge HE-6 (induced by source paper "power aware wireless file downloading a constrained restless bandit approach"):
  with members:
    - "exploiting channel memory for joint estimation and scheduling in downlink networks"
    - "throughput optimal opportunistic scheduling in the presence of flow level dynamics"

Connected through hyperedge HE-7 (induced by source paper "urop a simple near optimal scheduling policy for energy harvesting sensors"):
  with members:
    - "multi channel opportunistic access a case of restless bandits with multiple plays"

Connected through hyperedge HE-8 (induced by source paper "sufficient conditions on the optimality of myopic sensing in opportunistic channel access a unifying framework"):
  with members:
    - "on optimality of myopic policy for restless multi armed bandit problem an axiomatic approach"
    - "on optimality of myopic sensing policy with imperfect sensing in multi channel opportunistic access"
    - "multi channel opportunistic access a case of restless bandits with multiple plays"
    - "on myopic sensing for multi channel opportunistic access structure optimality and performance"
    - "approximation algorithms for restless bandit problems"

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.NI(Networking and Internet Architecture)