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: "from dissipativity theory to compositional construction of finite markov decision processes"
  Abstract: This paper is concerned with a compositional approach for constructing finite Markov decision processes of interconnected discrete-time stochastic control systems. The proposed approach leverages the interconnection topology and a notion of so-called stochastic storage functions describing joint dissipativity-type properties of subsystems and their abstractions. In the first part of the paper, we derive dissipativity-type compositional conditions for quantifying the error between the interconnection of stochastic control subsystems and that of their abstractions. In the second part of the paper, we propose an approach to construct finite Markov decision processes together with their corresponding stochastic storage functions for classes of discrete-time control systems satisfying some incremental passivablity property. Under this property, one can construct finite Markov decision processes by a suitable discretization of the input and state sets. Moreover, we show that for linear stochastic control systems, the aforementioned property can be readily checked by some matrix inequality. We apply our proposed results to the temperature regulation in a circular building by constructing compositionally a finite Markov decision process of a network containing 200 rooms in which the compositionality condition does not require any constraint on the number or gains of the subsystems. We employ the constructed finite Markov decision process as a substitute to synthesize policies regulating the temperature in each room for a bounded time horizon.

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"
    - "compositional synthesis of finite state abstractions"
    - "dynamic bayesian networks as formal abstractions of structured stochastic processes"

Connected through hyperedge HE-2 (induced by source paper "compositional in finite abstractions for large scale interconnected stochastic systems"):
  with members:
    - "compositional abstraction based synthesis of general mdps via approximate probabilistic relations"
    - "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 synthesis of symbolic models"
    - "compositional abstraction and safety synthesis using overlapping symbolic models"
    - "dynamic bayesian networks as formal abstractions of structured stochastic processes"

Connected through hyperedge HE-3 (induced by source paper "compositional construction of infinite abstractions for networks of stochastic control systems"):
  with members:
    - "robust dynamic programming for temporal logic control of stochastic systems"
    - "compositional in finite abstractions for large scale interconnected stochastic systems"
    - "compositional abstractions of interconnected discrete time stochastic control systems"
    - "compositional construction of finite state abstractions for stochastic control systems"
    - "dynamic bayesian networks as formal abstractions of structured stochastic processes"

Connected through hyperedge HE-4 (induced by source paper "temporal logic verification of stochastic systems using barrier certificates"):
  with members:
    - "dynamic bayesian networks as formal abstractions of structured stochastic processes"
    - "faust 2 f ormal abstractions of uncountable state stochastic processes"
    - "automata theory meets barrier certificates temporal logic verification of nonlinear systems"

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)