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: "on the non existence of nash equilibrium in games with resource bounded players"
  Abstract: We consider sequences of games $\mathcal{G}=\{G_1,G_2,\ldots\}$ where, for all $n$, $G_n$ has the same set of players. Such sequences arise in the analysis of running time of players in games, in electronic money systems such as Bitcoin and in cryptographic protocols. Assuming that one-way functions exist, we prove that there is a sequence of 2-player zero-sum Bayesian games $\mathcal{G}$ such that, for all $n$, the size of every action in $G_n$ is polynomial in $n$, the utility function is polynomial computable in $n$, and yet there is no polynomial-time Nash equilibrium, where we use a notion of Nash equilibrium that is tailored to sequences of games. We also demonstrate that Nash equilibrium may not exist when considering players that are constrained to perform at most $T$ computational steps in each of the games $\{G_i\}_{i=1}^{\infty}$. These examples may shed light on competitive settings where the availability of more running time or faster algorithms lead to a "computational arms race", precluding the existence of equilibrium. They also point to inherent limitations of concepts such "best response" and Nash equilibrium in games with resource-bounded players.

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"
    - "an axiomatic approach to block rewards"
    - "reward sharing schemes for stake pools"
    - "compounding of wealth in proof of stake cryptocurrencies"

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)