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: "sequential convex programming for the efficient verification of parametric mdps"
  Abstract: Multi-objective verification problems of parametric Markov decision processes under optimality criteria can be naturally expressed as nonlinear programs. We observe that many of these computationally demanding problems belong to the subclass of signomial programs. This insight allows for a sequential optimization algorithm to efficiently compute sound but possibly suboptimal solutions. Each stage of this algorithm solves a geometric programming problem. These geometric programs are obtained by convexifying the nonconvex constraints of the original problem. Direct applications of the encodings as nonlinear pro- grams are model repair and parameter synthesis. We demonstrate the scalability and quality of our approach by well-known benchmarks

Connected through hyperedge HE-1 (induced by source paper "parameter synthesis for markov models"):
  with members:
    - "shepherding hordes of markov chains"
    - "parameter independent strategies for pmdps via pomdps"
    - "sea param exploring schedulers in parametric mdps"
    - "multi objective robust strategy synthesis for interval markov decision processes"
    - "parametric markov chains pctl complexity and fraction free gaussian elimination"
    - "reachability in augmented interval markov chains"
    - "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 "scenario based verification of uncertain mdps"):
  with members:
    - "parameter synthesis for markov models"
    - "parameter independent strategies for pmdps via pomdps"
    - "incremental verification of parametric and reconfigurable markov chains"
    - "a storm is coming a modern probabilistic model checker"
    - "multi objective approaches to markov decision processes with uncertain transition parameters"
    - "parameter synthesis for markov models faster than ever"
    - "incremental pruning a simple fast exact method for partially observable markov decision processes"

Connected through hyperedge HE-3 (induced by source paper "parameter independent strategies for pmdps via pomdps"):
  with members:
    - "sea param exploring schedulers in parametric mdps"
    - "automated experiment design for data efficient verification of parametric markov decision processes"
    - "a storm is coming a modern probabilistic model checker"
    - "ares adaptive receding horizon synthesis of optimal plans"
    - "parameter synthesis for markov models faster than ever"
    - "a symbolic sat based algorithm for almost sure reachability with small strategies in pomdps"
    - "optimal cost almost sure reachability in pomdps"
    - "pomdps under probabilistic semantics"

Connected through hyperedge HE-4 (induced by source paper "structured synthesis for probabilistic systems"):
  with members:
    - "shepherding hordes of markov chains"
    - "a storm is coming a modern probabilistic model checker"
    - "parameter synthesis for markov models faster than ever"
    - "high level counterexamples for probabilistic automata"
    - "pareto curves for probabilistic model checking"
    - "multi objective model checking of markov decision processes"

Connected through hyperedge HE-5 (induced by source paper "accelerated model checking of parametric markov chains"):
  with members:
    - "the power of synchronisation formal analysis of power consumption in networks of pulse coupled oscillators"
    - "a storm is coming a modern probabilistic model checker"
    - "parameter synthesis for markov models faster than ever"
    - "synthesizing systems with optimal average case behavior for ratio objectives"

Connected through hyperedge HE-6 (induced by source paper "parameter and insertion function co synthesis for opacity enhancement in parametric stochastic discrete event systems"):
  with members:
    - "parameter synthesis for markov models faster than ever"

Connected through hyperedge HE-7 (induced by source paper "permissive finite state controllers of pomdps using parameter synthesis"):
  with members:
    - "parametric markov chains pctl complexity and fraction free gaussian elimination"
    - "a storm is coming a modern probabilistic model checker"
    - "parameter synthesis for markov models faster than ever"
    - "safety constrained reinforcement learning for mdps"
    - "permissive controller synthesis for probabilistic systems"
    - "a symbolic sat based algorithm for almost sure reachability with small strategies in pomdps"
    - "optimal cost almost sure reachability in pomdps"
    - "solving pomdps by searching the space of finite policies"

Connected through hyperedge HE-8 (induced by source paper "sea param exploring schedulers in parametric mdps"):
  with members:
    - "parameter synthesis for markov models faster than ever"
    - "smoothed model checking for uncertain continuous time markov chains"
    - "accelerating parametric probabilistic verification"

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)