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: "lazy probabilistic model checking without determinisation"
  Abstract: The bottleneck in the quantitative analysis of Markov chains and Markov decision processes against specifications given in LTL or as some form of nondeterministic B\"uchi automata is the inclusion of a determinisation step of the automaton under consideration. In this paper, we show that full determinisation can be avoided: subset and breakpoint constructions suffice. We have implemented our approach---both explicit and symbolic versions---in a prototype tool. Our experiments show that our prototype can compete with mature tools like PRISM.

Connected through hyperedge HE-1 (induced by source paper "control synthesis from linear temporal logic specifications using model free reinforcement learning"):
  with members:
    - "logically constrained reinforcement learning"
    - "omega regular objectives in model free reinforcement learning"
    - "foundations for restraining bolts reinforcement learning with ltlf ldlf restraining specifications"
    - "a policy search method for temporal logic specified reinforcement learning tasks"
    - "probabilistic motion planning under temporal tasks and soft constraints"
    - "q learning for robust satisfaction of signal temporal logic specifications"
    - "reinforcement learning with temporal logic rewards"
    - "correct by synthesis reinforcement learning with temporal logic constraints"

Connected through hyperedge HE-2 (induced by source paper "good for mdps automata for probabilistic analysis and reinforcement learning"):
  with members:
    - "omega regular objectives in model free reinforcement learning"
    - "proximal policy optimization algorithms"
    - "adam a method for stochastic optimization"
    - "determinising parity automata"
    - "state of buchi complementation"

Connected through hyperedge HE-3 (induced by source paper "good for mdps automata"):
  with members:
    - "omega regular objectives in model free reinforcement learning"
    - "state of buchi complementation"
    - "ltl to b uchi automata translation fast and more deterministic"

Connected through hyperedge HE-4 (induced by source paper "from ltl to unambiguous b uchi automata via disambiguation of alternating automata"):
  with members:
    - "ltl store repository of ltl formulae from literature and case studies"
    - "ltl to deterministic emerson lei automata"

Connected through hyperedge HE-5 (induced by source paper "omega regular objectives in model free reinforcement learning"):
  with members:
    - "certified reinforcement learning with logic guidance"
    - "an investigation of model free planning"
    - "logically correct reinforcement learning"
    - "reinforcement learning with temporal logic rewards"
    - "verification of markov decision processes using learning algorithms"
    - "a learning based approach to control synthesis of markov decision processes for linear temporal logic specifications"
    - "probably approximately correct mdp learning and control with temporal logic constraints"
    - "automata with generalized rabin pairs for probabilistic model checking and ltl synthesis"

Connected through hyperedge HE-6 (induced by source paper "one theorem to rule them all a unified translation of ltl into ω automata"):
  with members:
    - "index appearance record for transforming rabin automata into parity automata"
    - "from ltl and limit deterministic b uchi automata to deterministic parity automata"
    - "from ltl to deterministic automata a safraless compositional approach"
    - "automata with generalized rabin pairs for probabilistic model checking and ltl synthesis"
    - "effective translation of ltl to deterministic rabin automata beyond the f g fragment"
    - "deterministic automata for the f g fragment of ltl"
    - "from nondeterministic b uchi and streett automata to deterministic parity automata"

Connected through hyperedge HE-7 (induced by source paper "synthesising strategy improvement and recursive algorithms for solving 2 5 player parity games"):
  with members:
    - "symmetric strategy improvement"
    - "non oblivious strategy improvement"
    - "gist a solver for probabilistic games"
    - "solving simple stochastic games with few random vertices"
    - "relational parametricity for computational effects"

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.LO(Logic in Computer Science)