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: "shield synthesis runtime enforcement for reactive systems"
  Abstract: Scalability issues may prevent users from verifying critical properties of a complex hardware design. In this situation, we propose to synthesize a "safety shield" that is attached to the design to enforce the properties at run time. Shield synthesis can succeed where model checking and reactive synthesis fail, because it only considers a small set of critical properties, as opposed to the complex design, or the complete specification in the case of reactive synthesis. The shield continuously monitors the input/output of the design and corrects its erroneous output only if necessary, and as little as possible, so other non-critical properties are likely to be retained. Although runtime enforcement has been studied in other domains such as action systems, reactive systems pose unique challenges where the shield must act without delay. We thus present the first shield synthesis solution for reactive hardware systems and report our experimental results. This is an extended version of [5], featuring an additional appendix.

Connected through hyperedge HE-1 (induced by source paper "an inductive synthesis framework for verifiable reinforcement learning"):
  with members:
    - "concolic testing for deep neural networks"
    - "programmatically interpretable reinforcement learning"
    - "reachability analysis of deep neural networks with provable guarantees"
    - "verifiable reinforcement learning via policy extraction"
    - "feature guided black box safety testing of deep neural networks"
    - "deep reinforcement learning an overview"
    - "towards generalization and simplicity in continuous control"
    - "reluplex an efficient smt solver for verifying deep neural networks"

Connected through hyperedge HE-2 (induced by source paper "specification and reactive synthesis of robust controllers"):
  with members:
    - "reactive control meets runtime verification a case study of navigation"
    - "formalizing timing diagram requirements in discrete duration calulus"
    - "how to handle assumptions in synthesis"

Connected through hyperedge HE-3 (induced by source paper "shielded decision making in mdps"):
  with members:
    - "logically constrained reinforcement learning"
    - "maximizing the conditional expected reward for reaching the goal"
    - "a storm is coming a modern probabilistic model checker"
    - "safe reinforcement learning via shielding"
    - "a berkeley view of systems challenges for ai"
    - "concrete problems in ai safety"
    - "correct by synthesis reinforcement learning with temporal logic constraints"
    - "safety constrained reinforcement learning for mdps"

Connected through hyperedge HE-4 (induced by source paper "structural synthesis for gxw specifications"):
  with members:
    - "g4ltl st automatic generation of plc programs"
    - "how to handle assumptions in synthesis"
    - "abssynthe abstract synthesis from succinct safety specifications"

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)