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: "high level counterexamples for probabilistic automata"
  Abstract: Providing compact and understandable counterexamples for violated system#N#properties is an essential task in model checking. Existing works on#N#counterexamples for probabilistic systems so far computed either a large set of#N#system runs or a subset of the system's states, both of which are of limited#N#use in manual debugging. Many probabilistic systems are described in a guarded#N#command language like the one used by the popular model checker PRISM. In this#N#paper we describe how a smallest possible subset of the commands can be#N#identified which together make the system erroneous. We additionally show how#N#the selected commands can be further simplified to obtain a well-understandable#N#counterexample.

Connected through hyperedge HE-1 (induced by source paper "the probabilistic model checker storm"):
  with members:
    - "counterexample driven synthesis for probabilistic program sketches"
    - "safety analysis for vehicle guidance systems with dynamic fault trees"
    - "parameter synthesis for markov models"
    - "value iteration for long run average reward in markov decision processes"
    - "markov automata with multiple objectives"
    - "maximizing the conditional expected reward for reaching the goal"
    - "a storm is coming a modern probabilistic model checker"
    - "parameter synthesis for markov models faster than ever"

Connected through hyperedge HE-2 (induced by source paper "counterexample driven synthesis for probabilistic program sketches"):
  with members:
    - "shepherding hordes of markov chains"
    - "structured synthesis for probabilistic systems"
    - "safety aware apprenticeship learning"
    - "a storm is coming a modern probabilistic model checker"
    - "parameter synthesis for markov models faster than ever"
    - "safety constrained reinforcement learning for mdps"
    - "a symbolic sat based algorithm for almost sure reachability with small strategies in pomdps"
    - "optimal cost almost sure reachability in pomdps"

Connected through hyperedge HE-3 (induced by source paper "human in the loop synthesis for partially observable markov decision processes"):
  with members:
    - "permissive finite state controllers of pomdps using parameter synthesis"
    - "a storm is coming a modern probabilistic model checker"
    - "motion planning under partial observability using game based abstraction"
    - "synthesis of shared control protocols with provable safety and performance guarantees"
    - "optimal cost almost sure reachability in pomdps"
    - "qualitative analysis of pomdps with temporal logic specifications for robotics applications"
    - "solving pomdps by searching the space of finite policies"
    - "heuristic search value iteration for pomdps"

Connected through hyperedge HE-4 (induced by source paper "structured synthesis for probabilistic systems"):
  with members:
    - "shepherding hordes of markov chains"
    - "sequential convex programming for the efficient verification of parametric mdps"
    - "a storm is coming a modern probabilistic model checker"
    - "parameter synthesis for markov models faster than ever"
    - "pareto curves for probabilistic model checking"
    - "multi objective model checking of markov decision processes"

Connected through hyperedge HE-5 (induced by source paper "the power of convex algebras"):
  with members:
    - "termination in convex sets of distributions"
    - "a convenient category for higher order probability theory"
    - "robust synchronization in markov decision processes"
    - "probabilistic bisimulation naturally on distributions"
    - "coinduction up to in a fibrational setting"
    - "when equivalence and bisimulation join forces in probabilistic automata"
    - "church a language for generative models"
    - "relating coalgebraic notions of bisimulation"

Connected through hyperedge HE-6 (induced by source paper "a storm is coming a modern probabilistic model checker"):
  with members:
    - "parameter synthesis for markov models faster than ever"
    - "extracting verified decision procedures dpll and resolution"
    - "safety constrained reinforcement learning for mdps"
    - "permissive controller synthesis for probabilistic systems"
    - "analysis of timed and long run objectives for markov automata"
    - "verification of markov decision processes using learning algorithms"
    - "a robust class of data languages and an application to learning"

Connected through hyperedge HE-7 (induced by source paper "bounded model checking for probabilistic programs"):
  with members:
    - "parameter synthesis for markov models faster than ever"
    - "inferring covariances for probabilistic programs"
    - "reasoning about recursive probabilistic programs"
    - "on the hardness of almost sure termination"

Connected through hyperedge HE-8 (induced by source paper "debugging of markov decision processes mdps models"):
  with members:
    - "causes and explanations in the structural model approach tractable cases"
    - "responsibility and blame a structural model approach"

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.SE(Software Engineering)