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: "aspiration learning in coordination games"
  Abstract: We consider the problem of distributed convergence to efficient outcomes in coordination games through dynamics based on aspiration learning. Our first contribution is the characterization of the asymptotic behavior of the induced Markov chain of the iterated process in terms of an equivalent finite-state Markov chain. We then characterize explicitly the behavior of the proposed aspiration learning in a generalized version of coordination games, examples of which include network formation and common-pool games. In particular, we show that in generic coordination games the frequency at which an efficient action profile is played can be made arbitrarily large. Although convergence to efficient outcomes is desirable, in several coordination games, such as common-pool games, attainability of fair outcomes, i.e., sequences of plays at which players experience highly rewarding returns with the same frequency, might also be of special interest. To this end, we demonstrate through analysis and simulations that aspiration learning also establishes fair outcomes in all symmetric coordination games, including common-pool games.#N##N##N#Read More: http://epubs.siam.org/doi/abs/10.1137/110852462

Connected through hyperedge HE-1 (induced by source paper "learning based dynamic pinning of parallelized applications in many core systems"):
  with members:
    - "measurement based efficient resource allocation with demand side adjustments"
    - "an evolutionary stochastic local search framework for one dimensional cutting stock problems"
    - "stochastic stability of perturbed learning automata in positive utility games"
    - "efficient dynamic pinning of parallelized applications by distributed reinforcement learning"
    - "on the structure of weakly acyclic games"

Connected through hyperedge HE-2 (induced by source paper "volunteers in the smart city comparison of contribution strategies on human centered measures"):
  with members:
    - "privacy enhancing aggregation of internet of things data via sensors grouping"
    - "motivating smartphone collaboration in data acquisition and distributed computing"
    - "evolutionary algorithms for reinforcement learning"

Connected through hyperedge HE-3 (induced by source paper "aspiration based perturbed learning automata"):
  with members:
    - "stochastic stability of perturbed learning automata in positive utility games"

Connected through hyperedge HE-4 (induced by source paper "measurement based efficient resource allocation with demand side adjustments"):
  with members:
    - "stochastic stability of perturbed learning automata in positive utility games"
    - "regression models for output prediction of thermal dynamics in buildings"

Connected through hyperedge HE-5 (induced by source paper "stochastic stability of perturbed learning automata in positive utility games"):
  with members:
    - "stochastic stability analysis of perturbed learning automata with constant step size in strategic form games"

Connected through hyperedge HE-6 (induced by source paper "learning in repeated games human versus machine"):
  with members:
    - "a polynomial time nash equilibrium algorithm for repeated stochastic 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)