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 "coalition safe equilibria with virtual payoffs"):
  Abstract: Consider a set of parties invited to execute a protocol $\Pi$. The protocol will incur some cost to run while in the end (or at regular intervals), it will populate and update local tables that assign (virtual) rewards to participants. Each participant aspires to offset the costs of participation by these virtual payoffs that are provided in the course of the protocol. In this setting, we introduce and study a notion of coalition-safe equilibrium. In particular, we consider a strategic coalition of participants that is centrally coordinated and potentially deviates from $\Pi$ with the objective to increase its utility with respect to the view of {\em at least one} of the other participants. The protocol $\Pi$ is called a coalition-safe equilibrium with virtual payoffs (EVP) if no such protocol deviation exists. We apply our notion to study incentives in blockchain protocols. We proceed to use our framework to provide a unified picture of incentives in the Bitcoin blockchain, for absolute and relative rewards based utility functions, as well as prove novel results regarding incentives of the Fruitchain blockchain protocol [PODC 2017] showing that the equilibrium condition holds for collusions up to $n-1$ players for absolute rewards based utility functions and less than $n/2$ for relative rewards based utility functions, with the latter result holding for any "weakly fair" blockchain protocol, a new property that we introduce and may be of independent interest.

Includes members:
  Member "presto a systematic framework for blockchain consensus protocols":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the security reference architecture for blockchains towards a standardized model for studying vulnerabilities threats and defenses")
  Member "squirrl automating attack discovery on blockchain incentive mechanisms with deep reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the convergence of artificial intelligence and distributed ledger technology a scoping review and future research agenda")
  Member "the gap game":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "incentive analysis of bitcoin ng revisited")
  Member "blockchain mining games":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the feasibility of sybil attacks in shard based permissionless blockchains")
  Member "optimal selfish mining strategies in bitcoin":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "incentive analysis of bitcoin ng revisited")
  Member "majority is not enough bitcoin mining is vulnerable":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the convergence of artificial intelligence and distributed ledger technology a scoping review and future research agenda")
  Member "on bitcoin and red balloons":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "surface a practical blockchain consensus algorithm for real world networks")
  Member "an almost surely terminating polynomial protocol for asynchronous byzantine agreement with optimal resilience":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "security in asynchronous interactive systems")

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)