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: "heterogeneous learning in zero sum stochastic games with incomplete information"
  Abstract: Learning algorithms are essential for the applications of game theory in a networking environment. In dynamic and decentralized settings where the traffic, topology and channel states may vary over time and the communication between agents is impractical, it is important to formulate and study games of incomplete information and fully distributed learning algorithms which for each agent requires a minimal amount of information regarding the remaining agents. In this paper, we address this major challenge and introduce heterogeneous learning schemes in which each agent adopts a distinct learning pattern in the context of games with incomplete information. We use stochastic approximation techniques to show that the heterogeneous learning schemes can be studied in terms of their deterministic ordinary differential equation (ODE) counterparts. Depending on the learning rates of the players, these ODEs could be different from the standard replicator dynamics, (myopic) best response (BR) dynamics, logit dynamics, and fictitious play dynamics. We apply the results to a class of security games in which the attacker and the defender adopt different learning schemes due to differences in their rationality levels and the information they acquire.

Connected through hyperedge HE-1 (induced by source paper "game theory for cyber deception a tutorial"):
  with members:
    - "modeling analysis and mitigation of dynamic botnet formation in wireless iot networks"
    - "game theoretic analysis of cyber deception evidence based strategies and dynamic risk mitigation"
    - "dynamic bayesian games for adversarial and defensive cyber deception"
    - "adaptive strategic cyber defense for advanced persistent threats in critical infrastructure networks"
    - "game theory meets network security a tutorial"
    - "modeling and analysis of leaky deception using signaling games with evidence"
    - "istrict an interdependent strategic trust mechanism for the cloud enabled internet of controlled things"
    - "a dynamic game analysis and design of infrastructure network protection and recovery 125"

Connected through hyperedge HE-2 (induced by source paper "strategic learning for active adaptive and autonomous cyber defense"):
  with members:
    - "modeling analysis and mitigation of dynamic botnet formation in wireless iot networks"
    - "adaptive honeypot engagement through reinforcement learning of semi markov decision processes"
    - "a dynamic games approach to proactive defense strategies against advanced persistent threats in cyber physical systems"
    - "adaptive strategic cyber defense for advanced persistent threats in critical infrastructure networks"
    - "modeling and analysis of leaky deception using signaling games with evidence"
    - "optimal timing in dynamic and robust attacker engagement during advanced persistent threats"
    - "a dynamic game analysis and design of infrastructure network protection and recovery 125"
    - "a game theoretic taxonomy and survey of defensive deception for cybersecurity and privacy"

Connected through hyperedge HE-3 (induced by source paper "multilayer cyber physical security and resilience for smart grid"):
  with members:
    - "a game theoretic framework for resilient and distributed generation control of renewable energies in microgrids"
    - "a stackelberg game approach for two level distributed energy management in smart grids"
    - "flip the cloud cyber physical signaling games in the presence of advanced persistent threats"
    - "prices of anarchy information and cooperation in differential games"
    - "dynamic interference minimization routing game for on demand cognitive pilot channel"

Connected through hyperedge HE-4 (induced by source paper "game theory meets network security a tutorial"):
  with members:
    - "adaptive strategic cyber defense for advanced persistent threats in critical infrastructure networks"
    - "modeling and analysis of leaky deception using signaling games with evidence"
    - "a mean field stackelberg game approach for obfuscation adoption in empirical risk minimization"
    - "proactive defense against physical denial of service attacks using poisson signaling games"
    - "a dynamic game analysis and design of infrastructure network protection and recovery 125"
    - "a stackelberg game perspective on the conflict between machine learning and data obfuscation"
    - "deception by design evidence based signaling games for network defense"
    - "flip the cloud cyber physical signaling games in the presence of advanced persistent threats"

Connected through hyperedge HE-5 (induced by source paper "distributed evaluation and convergence of self appraisals in social networks"):
  with members:
    - "game theoretic analysis of the hegselmann krause model for opinion dynamics in finite dimensions"
    - "consensus with linear objective maps"
    - "opinion fluctuations and disagreement in social networks"
    - "opinion dynamics in social networks a local interaction game with stubborn agents"

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.LG(Machine Learning)