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 "local distributed algorithms for selfish agents"):
  Abstract: In the classical framework of local distributed network computing, it is generally assumed that the entities executing distributed algorithms are altruistic. However, in various scenarios, the value of the output produced by an entity may have a tremendous impact on its future. This is for instance the case of tasks such as computing maximal independent sets (MIS) in networks. Indeed, a node belonging to the MIS may be later asked more than to a node not in the MIS, e.g., because MIS in networks are often used as backbones to collect, transfer, and broadcast information, which is costly. In this paper, we revisit typical local distributed network computing tasks in the framework of algorithmic game theory. Specifically, we focus on the construction of solutions for locally checkable labeling (LCL) tasks, which form a large class of distributed tasks, including MIS, coloring, maximal matching, etc., and which have been studied for more than 20 years in distributed computing. #R##N#Given an LCL task, the nodes are collectively aiming at computing a solution, but, at the individual level, every node plays rationally and selfishly with the objective of optimizing its own profit. Surprisingly, the classical frameworks for game theory are not fully appropriate for the purpose of our study. Moreover, we show that classical notions like Nash equilibria may yield algorithms requiring an arbitrarily large number of rounds to converge. Nevertheless, by extending and generalizing core results from game theory, we establish the existence of a so-called trembling-hand perfect equilibria, a subset of Nash equilibria that is well suited to LCL construction tasks. The main outcome of the paper is therefore that, for essentially all distributed tasks whose solutions are locally checkable, there exist construction algorithms which are robust to selfishness.

Includes members:
  Member "an exponential separation between randomized and deterministic complexity in the local model":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "truly tight in delta bounds for bipartite maximal matching and variants")
  Member "an improved distributed algorithm for maximal independent set":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "space efficient approximation to maximum matching size from uniform edge samples")

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.DC(Distributed, Parallel, and Cluster Computing)