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: "iterated regret minimization in game graphs"
  Abstract: Iterated regret minimization has been introduced recently by J.Y. Halpern and R. Pass in classical strategic games. For many games of interest, this new solution concept provides solutions that are judged more reasonable than solutions offered by traditional game concepts -- such as Nash equilibrium --. Although computing iterated regret on explicit matrix game is conceptually and computationally easy, nothing is known about computing the iterated regret on games whose matrices are defined implicitly using game tree, game DAG or, more generally game graphs. In this paper, we investigate iterated regret minimization for infinite duration two-player quantitative non-zero sum games played on graphs. #R##N#We consider reachability objectives that are not necessarily antagonist. Edges are weighted by integers -- one for each player --, and the payoffs are defined by the sum of the weights along the paths. Depending on the class of graphs, we give either polynomial or pseudo-polynomial time algorithms to compute a strategy that minimizes the regret for a fixed player. We finally give algorithms to compute the strategies of the two players that minimize the iterated regret for trees, and for graphs with strictly positive weights only.

Connected through hyperedge HE-1 (induced by source paper "the impatient may use limited optimism to minimize regret"):
  with members:
    - "ergodic mean payoff games for the analysis of attacks in crypto currencies"
    - "on delay and regret determinization of max plus automata"
    - "admissibility in quantitative graph games"
    - "reactive synthesis without regret"
    - "non zero sum games for reactive synthesis"
    - "minimizing regret in discounted sum games"

Connected through hyperedge HE-2 (induced by source paper "non zero sum games for reactive synthesis"):
  with members:
    - "weak subgame perfect equilibria and their application to quantitative reachability"
    - "assume admissible synthesis"
    - "reactive synthesis without regret"
    - "multidimensional beyond worst case and almost sure problems for mean payoff objectives"
    - "variations on the stochastic shortest path problem"
    - "secure equilibria in weighted games"
    - "percentile queries in multi dimensional markov decision processes"
    - "expectations or guarantees i want it all a crossroad between games and mdps"

Connected through hyperedge HE-3 (induced by source paper "reactive synthesis without regret"):
  with members:
    - "correct by synthesis reinforcement learning with temporal logic constraints"
    - "exact and approximate determinization of discounted sum automata"
    - "first cycle games"
    - "doomsday equilibria for omega regular games"
    - "generalized mean payoff and energy games"

Connected through hyperedge HE-4 (induced by source paper "minimizing regret in discounted sum games"):
  with members:
    - "reactive synthesis without regret"
    - "exact and approximate determinization of discounted sum automata"

Connected through hyperedge HE-5 (induced by source paper "robust equilibria in concurrent games"):
  with members:
    - "the complexity of nash equilibria in limit average games"
    - "the complexity of nash equilibria in simple stochastic multiplayer games"
    - "algorithms for omega regular games with imperfect information"

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)