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: "compositional synthesis of finite state abstractions"
  Abstract: Controller synthesis techniques for continuous systems with respect to temporal logic specifications typically use an intermediate finite-state symbolic abstraction of the system model. Constructing this abstraction for the entire system is computationally expensive, and does not exploit natural decompositions of many systems into interacting components. We describe a methodology for compositional symbolic abstraction to help scale controller synthesis for temporal logic to larger systems. #R##N#We introduce a new relation, called disturbance bisimulation, as the basis for compositional symbolic abstractions. Disturbance bisimulation strengthens the typically used $\varepsilon$-approximate alternating bisimulation relation. Using this relation we prove two main theorems. The first, called simultaneous approximation, shows how one can construct finite-state abstractions compositionally for each component, so that the abstractions are simultaneously disturbance bisimilar to their continuous counterparts. The second, called composition of approximation, shows an approximate bisimulation relationship between compositions of the finite symbolic models and the composition of the original network, when a small-gain condition is satisfied. #R##N#Our results are non-trivial because each component's dynamics is influenced by the states of other interacting components, whose values are only approximately known. We discuss how we get a compositional controller synthesis methodology for networks of such systems against local temporal specifications as a by-product of our construction.

Connected through hyperedge HE-1 (induced by source paper "compositional abstraction based synthesis of general mdps via approximate probabilistic relations"):
  with members:
    - "temporal logic control of general markov decision processes by approximate policy refinement"
    - "robust dynamic programming for temporal logic control of stochastic systems"
    - "compositional construction of infinite abstractions for networks of stochastic control systems"
    - "compositional abstractions of interconnected discrete time stochastic control systems"
    - "from dissipativity theory to compositional construction of finite markov decision processes"
    - "dynamic bayesian networks as formal abstractions of structured stochastic processes"

Connected through hyperedge HE-2 (induced by source paper "synthesizing functional reactive programs"):
  with members:
    - "vehicle platooning simulations with functional reactive programming"
    - "juniper a functional reactive programming language for the arduino"
    - "program synthesis from polymorphic refinement types"
    - "parameterized synthesis case study amba ahb"

Connected through hyperedge HE-3 (induced by source paper "compositional construction of finite state abstractions for stochastic control systems"):
  with members:
    - "dynamic bayesian networks as formal abstractions of structured stochastic processes"

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.SY(Systems and Control)