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 "artificial intelligence based cognitive routing for cognitive radio networks"):
  Abstract: Cognitive radio networks (CRNs) are networks of nodes equipped with cognitive radios that can optimize performance by adapting to network conditions. Although various routing protocols incorporating varying degrees of adaptiveness and cognition have been proposed for CRNs, these works have mostly been limited by their system-level focus (that emphasizes optimization at the level of an individual cognitive radio system). The vision of CRNs as cognitive networks, however, requires that the research focus progresses from its current system-level fixation to the a network-wide optimization focus. This motivates the development of cognitive routing protocols envisioned as routing protocols that fully and seamlessly incorporate artificial intelligence (AI)-based techniques into their design. In this paper, we provide a self-contained exposition of various decision-theoretic and learning techniques from the field of AI and machine-learning that are relevant to the problem of cognitive routing in CRNs. Apart from providing necessary background, we present for each technique discussed in this paper their application in the context of CRNs in general and for the routing problem in particular. We also highlight challenges associated with these techniques and common pitfalls. Finally, open research issues and future directions of work are identified.

Includes members:
  Member "multicasting in cognitive radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on green multicasting over cognitive radio fading channels")
  Member "genetic algorithms in wireless networking techniques applications and issues":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "game theory for multi access edge computing survey use cases and future trends")
  Member "a cooperative bayesian nonparametric framework for primary user activity monitoring in cognitive radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a coalitional game for distributed inference in sensor networks with dependent observations")
  Member "dynamic interference minimization routing game for on demand cognitive pilot channel":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "game theory for cyber deception a tutorial")
  Member "beyond nash equilibrium solution concepts for the 21st century":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "resilient cyberphysical systems and their application drivers a technology roadmap")
  Member "energy efficient resource allocation in wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "game theory for multi access edge computing survey use cases and future trends")
  Member "reinforcement learning for adaptive routing":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "an action language for multi agent domains foundations")
  Member "reinforcement learning a survey":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "online fast adaptation and knowledge accumulation a new approach to continual learning")

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.NI(Networking and Internet Architecture)