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: "estimation with strategic sensors"
  Abstract: We introduce a model of estimation in the presence of strategic, self-interested sensors. We employ a game-theoretic setup to model the interaction between the sensors and the receiver. The cost function of the receiver is equal to the estimation error variance while the cost function of the sensor contains an extra term which is determined by its private information. We start by the single sensor case in which the receiver has access to a noisy but honest side information in addition to the message transmitted by a strategic sensor. We study both static and dynamic estimation problems. For both these problems, we characterize a family of equilibria in which the sensor and the receiver employ simple strategies. Interestingly, for the dynamic estimation problem, we find an equilibrium for which the strategic sensor uses a memory-less policy. We generalize the static estimation setup to multiple sensors with synchronous communication structure (i.e., all the sensors transmit their messages simultaneously). We prove the maybe surprising fact that, for the constructed equilibrium in affine strategies, the estimation quality degrades as the number of sensors increases. However, if the sensors are herding (i.e., copying each other policies), the quality of the receiver's estimation improves as the number of sensors increases. Finally, we consider the asynchronous communication structure (i.e., the sensors transmit their messages sequentially).

Connected through hyperedge HE-1 (induced by source paper "dynamic information design a simple problem on optimal sequential information disclosure"):
  with members:
    - "optimal dynamic information provision in traffic routing"
    - "information theoretic approach to strategic communication as a hierarchical game"

Connected through hyperedge HE-2 (induced by source paper "strategic communication with side information at the decoder"):
  with members:
    - "strong coordination of signals and actions over noisy channels with two sided state information"
    - "persuasion with limited communication capacity"
    - "information design for strategic coordination of autonomous devices with non aligned utilities"
    - "information theoretic approach to strategic communication as a hierarchical game"
    - "on the role of side information in strategic communication"
    - "persuasion with limited communication"
    - "algorithmic bayesian persuasion"
    - "empirical coordination with two sided state information and correlated source and state"

Connected through hyperedge HE-3 (induced by source paper "competitive statistical estimation with strategic data sources"):
  with members:
    - "optimal data acquisition for statistical estimation"
    - "statistical estimation with strategic data sources in competitive settings"
    - "informed truthfulness in multi task peer prediction"
    - "promoting truthful behavior in participatory sensing mechanisms"
    - "crowdsourced judgement elicitation with endogenous proficiency"
    - "optimal mechanisms for selling information"
    - "optimal crowdsourcing contests"

Connected through hyperedge HE-4 (induced by source paper "a game theoretic approach to adversarial linear support vector classification"):
  with members:
    - "adequacy of the gradient descent method for classifier evasion attacks"
    - "adversarial examples attacks and defenses for deep learning"
    - "adversarial machine learning at scale"
    - "distillation as a defense to adversarial perturbations against deep neural networks"
    - "algorithmic bayesian persuasion"
    - "evasion attacks against machine learning at test time"

Connected through hyperedge HE-5 (induced by source paper "optimal hierarchical signaling for quadratic cost measures and general distributions a copositive program characterization"):
  with members:
    - "robust sensor design against multiple attackers with misaligned control objectives"
    - "deception as defense framework for cyber physical systems"
    - "information theoretic approach to strategic communication as a hierarchical game"
    - "hierarchical multistage gaussian signaling games in noncooperative communication and control systems"
    - "algorithmic bayesian persuasion"
    - "gossip algorithms for distributed signal processing"

Connected through hyperedge HE-6 (induced by source paper "deception as defense framework for cyber physical systems"):
  with members:
    - "robust sensor design against multiple attackers with misaligned control objectives"
    - "information theoretic approach to strategic communication as a hierarchical game"
    - "a game theoretic taxonomy and survey of defensive deception for cybersecurity and privacy"

Connected through hyperedge HE-7 (induced by source paper "on the number of bins in equilibria for signaling games"):
  with members:
    - "information theoretic approach to strategic communication as a hierarchical game"
    - "crawford sobel meet lloyd max on the grid"

Connected through hyperedge HE-8 (induced by source paper "information theoretic limits of strategic communication"):
  with members:
    - "information design for strategic coordination of autonomous devices with non aligned utilities"
    - "information theoretic approach to strategic communication as a hierarchical game"
    - "persuasion with limited communication"
    - "algorithmic bayesian persuasion"
    - "constrained source coding with side information"
    - "nash codes for noisy channels"
    - "perfect output feedback in the two user decentralized interference channel"
    - "rate distortion theory for secrecy systems"

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.GT(Computer Science and Game Theory)