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 "information design in spatial resource competition"):
  Abstract: We consider the information design problem in spatial resource competition settings. Agents gather at a location deciding whether to move to another location for possibly higher level of resources, and the utility each agent gets by moving to the other location decreases as more agents move there. The agents do not observe the resource level at the other location while a principal does and the principal would like to carefully release this information to attract a proper number of agents to move. We adopt the Bayesian persuasion framework and analyze the principal's optimal signaling mechanism design problem. We study both private and public signaling mechanisms. For private signaling, we show the optimal mechanism can be computed in polynomial time with respect to the number of agents. Obtaining the optimal private mechanism involves two steps: first, solve a linear program to get the marginal probability each agent should be recommended to move; second, sample the moving agents satisfying the marginal probabilities with a sequential sampling procedure. For public signaling, we show the sender preferred equilibrium has a simple threshold structure and the optimal public mechanism with respect to the sender preferred equilibrium can be computed in polynomial time. We support our analytical results with numerical computations that show the optimal private and public signaling mechanisms achieve substantially higher social welfare compared with no information or full information benchmarks in many settings.

Includes members:
  Member "information signal design for incentivizing team formation":
    also connected through other hyperedges:
      (none)
  Member "targeting and signaling in ad auctions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "public bayesian persuasion being almost optimal and almost persuasive")
  Member "algorithmic persuasion with no externalities":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "public bayesian persuasion being almost optimal and almost persuasive")
  Member "computational aspects of private bayesian persuasion":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "public bayesian persuasion being almost optimal and almost persuasive")

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.GT(Computer Science and Game Theory)