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 automaton learning approach to solving safety games over infinite graphs"
  Abstract: We propose a method to construct finite-state reactive controllers for systems whose interactions with their adversarial environment are modeled by infinite-duration two-player games over (possibly) infinite graphs. The proposed method targets safety games with infinitely many states or with such a large number of states that it would be impractical---if not impossible---for conventional synthesis techniques that work on the entire state space. We resort to constructing finite-state controllers for such systems through an automata learning approach, utilizing a symbolic representation of the underlying game that is based on finite automata. Throughout the learning process, the learner maintains an approximation of the winning region (represented as a finite automaton) and refines it using different types of counterexamples provided by the teacher until a satisfactory controller can be derived (if one exists). We present a symbolic representation of safety games (inspired by regular model checking), propose implementations of the learner and teacher, and evaluate their performance on examples motivated by robotic motion planning in dynamic environments.

Connected through hyperedge HE-1 (induced by source paper "optimally resilient strategies in pushdown safety games"):
  with members:
    - "synthesizing optimally resilient controllers"
    - "summaries for context free games"
    - "quantitative games under failures"
    - "robust linear temporal logic"
    - "how to handle assumptions in synthesis"
    - "playing pushdown parity games in a hurry"
    - "better quality in synthesis through quantitative objectives"

Connected through hyperedge HE-2 (induced by source paper "semantic labelling and learning for parity game solving in ltl synthesis"):
  with members:
    - "bosy an experimentation framework for bounded synthesis"
    - "oink an implementation and evaluation of modern parity game solvers"
    - "the 4th reactive synthesis competition syntcomp 2017 benchmarks participants results"
    - "efficient parallel strategy improvement for parity games"
    - "from ltl and limit deterministic b uchi automata to deterministic parity automata"
    - "from ltl to deterministic automata a safraless compositional approach"
    - "from nondeterministic b uchi and streett automata to deterministic parity automata"

Connected through hyperedge HE-3 (induced by source paper "strategy representation by decision trees with linear classifiers"):
  with members:
    - "strategy representation by decision trees in reactive synthesis"
    - "a storm is coming a modern probabilistic model checker"
    - "the second reactive synthesis competition syntcomp 2015"
    - "counterexample explanation by learning small strategies in markov decision processes"
    - "extended aiger format for synthesis"
    - "measuring and synthesizing systems in probabilistic environments"

Connected through hyperedge HE-4 (induced by source paper "security aware synthesis using delayed action games"):
  with members:
    - "reactive control improvisation"
    - "strategy representation by decision trees in reactive synthesis"
    - "verification and control of partially observable probabilistic real time systems"
    - "integrating active sensing into reactive synthesis with temporal logic constraints under partial observations"
    - "delay games with wmso u winning conditions"

Connected through hyperedge HE-5 (induced by source paper "learning based synthesis of safety controllers"):
  with members:
    - "horn ice learning for synthesizing invariantsand contracts"
    - "strategy representation by decision trees in reactive synthesis"
    - "abstract learning frameworks for synthesis"

Connected through hyperedge HE-6 (induced by source paper "strategy representation by decision trees in reactive synthesis"):
  with members:
    - "the second reactive synthesis competition syntcomp 2015"
    - "counterexample explanation by learning small strategies in markov decision processes"
    - "learning invariants using decision trees"
    - "extended aiger format for synthesis"

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.FL(Formal Languages and Automata Theory)