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: "an axiomatic approach to block rewards"
  Abstract: Proof-of-work blockchains reward each miner for one completed block by an amount that is, in expectation, proportional to the number of hashes the miner contributed to the mining of the block. Is this proportional allocation rule optimal? And in what sense? And what other rules are possible? In particular, what are the desirable properties that any "good" allocation rule should satisfy? To answer these questions, we embark on an axiomatic theory of incentives in proof-of-work blockchains at the time scale of a single block. We consider desirable properties of allocation rules including: symmetry; budget balance (weak or strong); sybil-proofness; and various grades of collusion-proofness. We show that Bitcoin's proportional allocation rule is the unique allocation rule satisfying a certain system of properties, but this does not hold for slightly weaker sets of properties, or when the miners are not risk-neutral. We also point out that a rich class of allocation rules can be approximately implemented in a proof-of-work blockchain.

Connected through hyperedge HE-1 (induced by source paper "sok tools for game theoretic models of security for cryptocurrencies"):
  with members:
    - "oceanic games centralization risks and incentives in blockchain mining"
    - "a survey on consensus mechanisms and mining strategy management in blockchain networks"
    - "selfish mining in ethereum"
    - "impossibility of full decentralization in permissionless blockchains"
    - "squirrl automating attack discovery on blockchain incentive mechanisms with deep reinforcement learning"
    - "reward sharing schemes for stake pools"
    - "compounding of wealth in proof of stake cryptocurrencies"
    - "blockmania from block dags to consensus"

Connected through hyperedge HE-2 (induced by source paper "heb hybrid expenditure blockchain"):
  with members:
    - "mind the mining"
    - "squirrl automating attack discovery on blockchain incentive mechanisms with deep reinforcement learning"
    - "sbft a scalable and decentralized trust infrastructure"
    - "sbft a scalable decentralized trust infrastructure for blockchains"
    - "a survey on security and privacy issues of bitcoin"
    - "the gap game"
    - "bitcoin a natural oligopoly"
    - "be selfish and avoid dilemmas fork after withholding faw attacks on bitcoin"

Connected through hyperedge HE-3 (induced by source paper "reward sharing schemes for stake pools"):
  with members:
    - "a deep dive into bitcoin mining pools an empirical analysis of mining shares"
    - "impossibility of full decentralization in permissionless blockchains"
    - "cryptocurrency egalitarianism a quantitative approach"
    - "compounding of wealth in proof of stake cryptocurrencies"
    - "equilibrium computation in atomic splittable routing games with convex cost functions"
    - "bitcoin a natural oligopoly"
    - "socially optimal mining pools"
    - "blockchain mining games"

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)