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: "encodings of bounded synthesis"
  Abstract: The reactive synthesis problem is to compute a system satisfying a given specification in temporal logic. Bounded synthesis is the approach to bound the maximum size of the system that we accept as a solution to the reactive synthesis problem. As a result, bounded synthesis is decidable whenever the corresponding verification problem is decidable, and can be applied in settings where classic synthesis fails, such as in the synthesis of distributed systems. In this paper, we study the constraint solving problem behind bounded synthesis. We consider different reductions of the bounded synthesis problem of linear-time temporal logic (LTL) to constraint systems given as boolean formulas (SAT), quantified boolean formulas (QBF), and dependency quantified boolean formulas (DQBF). The reductions represent different trade-offs between conciseness and algorithmic efficiency. In the SAT encoding, both inputs and states of the system are represented explicitly; in QBF, inputs are symbolic and states are explicit; in DQBF, both inputs and states are symbolic. We evaluate the encodings systematically using benchmarks from the reactive synthesis competition (SYNTCOMP) and state-of-the-art solvers. Our key, and perhaps surprising, empirical finding is that QBF clearly dominates both SAT and DQBF.

Connected through hyperedge HE-1 (induced by source paper "fbsat automatic inference of minimal finite state models of function blocks using sat solver"):
  with members:
    - "bosy an experimentation framework for bounded synthesis"
    - "bounded cycle synthesis"
    - "learning moore machines from input output traces"
    - "g4ltl st automatic generation of plc programs"

Connected through hyperedge HE-2 (induced by source paper "learning heuristics for quantified boolean formulas through deep reinforcement learning"):
  with members:
    - "graph representations for higher order logic and theorem proving"
    - "understanding and extending incremental determinization for 2qbf"
    - "learning a sat solver from single bit supervision"
    - "automated theorem proving in intuitionistic propositional logic by deep reinforcement learning"
    - "can neural networks understand logical entailment"
    - "reinforcement learning of theorem proving"
    - "deep network guided proof search"
    - "learning continuous semantic representations of symbolic expressions"

Connected through hyperedge HE-3 (induced by source paper "reactive synthesis with maximum realizability of linear temporal logic specifications"):
  with members:
    - "maximum realizability for linear temporal logic specifications"
    - "robust linear temporal logic"
    - "low effort specification debugging and analysis"
    - "on the minimal revision problem of specification automata"
    - "better quality in synthesis through quantitative objectives"

Connected through hyperedge HE-4 (induced by source paper "synthesizing reactive systems from hyperproperties"):
  with members:
    - "bosy an experimentation framework for bounded synthesis"
    - "monitoring hyperproperties"
    - "the first order logic of hyperproperties"
    - "detecting unrealizability of distributed fault tolerant systems"
    - "a temporal logic for hyperproperties"

Connected through hyperedge HE-5 (induced by source paper "synthesis of coordination programs from linear temporal logic"):
  with members:
    - "bosy an experimentation framework for bounded synthesis"
    - "hennessy milner logic with greatest fixed points as a complete behavioural specification theory"
    - "ltl to b uchi automata translation fast and more deterministic"
    - "algorithms for omega regular games with imperfect information"

Connected through hyperedge HE-6 (induced by source paper "understanding and extending incremental determinization for 2qbf"):
  with members:
    - "on expansion and resolution in cegar based qbf solving"
    - "qbf solving by counterexample guided expansion"
    - "a theory of formal synthesis via inductive learning"

Connected through hyperedge HE-7 (induced by source paper "solving qbf by abstraction"):
  with members:
    - "bosy an experimentation framework for bounded synthesis"
    - "on expansion and resolution in cegar based qbf solving"
    - "the 4th reactive synthesis competition syntcomp 2017 benchmarks participants results"
    - "symbolic vs bounded synthesis for petri games"
    - "the first reactive synthesis competition syntcomp 2014"
    - "the 3rd reactive synthesis competition syntcomp 2016 benchmarks participants results"
    - "detecting unrealizability of distributed fault tolerant systems"
    - "petri games synthesis of distributed systems with causal memory"

Connected through hyperedge HE-8 (induced by source paper "expansion based qbf solving without recursion"):
  with members:
    - "evaluating qbf solvers quantifier alternations matter"
    - "on expansion and resolution in cegar based qbf solving"
    - "depqbf 6 0 a search based qbf solver beyond traditional qcdcl"
    - "structural synthesis for gxw specifications"
    - "detecting unrealizability of distributed fault tolerant systems"
    - "conformant planning as a case study of incremental qbf solving"

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)