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: "assume guarantee abstraction refinement for probabilistic systems"
  Abstract: We describe an automated technique for assume-guarantee style checking of strong simulation between a system and a specification, both expressed as non-deterministic Labeled Probabilistic Transition Systems (LPTSes). We first characterize counterexamples to strong simulation as stochastic trees and show that simpler structures are insufficient. Then, we use these trees in an abstraction refinement algorithm that computes the assumptions for assume-guarantee reasoning as conservative LPTS abstractions of some of the system components. The abstractions are automatically refined based on tree counterexamples obtained from failed simulation checks with the remaining components. We have implemented the algorithms for counterexample generation and assume-guarantee abstraction refinement and report encouraging results.

Connected through hyperedge HE-1 (induced by source paper "compositional verification for autonomous systems with deep learning components"):
  with members:
    - "dropout inference in bayesian neural networks with alpha divergences"
    - "deepsafe a data driven approach for checking adversarial robustness in neural networks"
    - "reluplex an efficient smt solver for verifying deep neural networks"
    - "compositional falsification of cyber physical systems with machine learning components"
    - "stochastic assume guarantee contracts for cyber physical system design under probabilistic requirements"
    - "safety verification of deep neural networks"
    - "towards evaluating the robustness of neural networks"
    - "adversarial examples in the physical world"

Connected through hyperedge HE-2 (induced by source paper "compositional abstraction refinement for control synthesis"):
  with members:
    - "synthesis of separable controlled invariant sets for modular local control design"
    - "an iterative abstraction algorithm for reactive correct by construction controller synthesis"
    - "abstractions and sensor design in partial information reactive controller synthesis"

Connected through hyperedge HE-3 (induced by source paper "efficient strategy iteration for mean payoff in markov decision processes"):
  with members:
    - "value iteration for long run average reward in markov decision processes"
    - "efficient parallel strategy improvement for parity games"
    - "synthesising strategy improvement and recursive algorithms for solving 2 5 player parity games"
    - "multigain a controller synthesis tool for mdps with multiple mean payoff objectives"
    - "verification of markov decision processes using learning algorithms"
    - "parametric strategy iteration"
    - "using strategy improvement to stay alive"
    - "the complexity of solving reachability games using value and strategy iteration"

Connected through hyperedge HE-4 (induced by source paper "value iteration for long run average reward in markov decision processes"):
  with members:
    - "multigain a controller synthesis tool for mdps with multiple mean payoff objectives"
    - "unifying two views on multiple mean payoff objectives in markov decision processes"
    - "knowledge spaces and the completeness of learning strategies"
    - "the complexity of ergodic mean payoff games"
    - "verification of markov decision processes using learning algorithms"
    - "markov decision processes with multiple long run averageobjectives"
    - "faster algorithms for markov decision processes with low treewidth"
    - "trading performance for stability in markov decision processes"

Connected through hyperedge HE-5 (induced by source paper "permissive supervisor synthesis for markov decision processes through learning"):
  with members:
    - "transfer entropy in mdps with temporal logic specifications"
    - "a learning based optimal human robot collaboration with linear temporal logic constraints"
    - "permissive controller synthesis for probabilistic systems"
    - "optimal and approximate q value functions for decentralized pomdps"

Connected through hyperedge HE-6 (induced by source paper "counterexample explanation by learning small strategies in markov decision processes"):
  with members:
    - "high level counterexamples for probabilistic automata"
    - "permissive controller synthesis for probabilistic systems"
    - "verification of markov decision processes using learning algorithms"
    - "cegar for qualitative analysis of probabilistic systems"
    - "spudd stochastic planning using decision diagrams"
    - "measuring permissiveness in parity games mean payoff parity games revisited"
    - "significant diagnostic counterexamples in probabilistic model checking"
    - "decision theoretic planning structural assumptions and computational leverage"

Connected through hyperedge HE-7 (induced by source paper "high level counterexamples for probabilistic automata"):
  with members:
    - "significant diagnostic counterexamples in probabilistic model checking"

Connected through hyperedge HE-8 (induced by source paper "cegar for qualitative analysis of probabilistic systems"):
  with members:
    - "the complexity of partial observation stochastic parity games with finite memory strategies"
    - "what is decidable about partially observable markov decision processes with omega regular objectives"
    - "interface simulation distances"
    - "faster algorithms for alternating refinement relations"
    - "decidable problems for probabilistic automata on infinite words"
    - "an o n 2 time algorithm for alternating b uchi games"
    - "partial observation stochastic games how to win when belief fails"
    - "qualitative analysis of partially observable markov decision 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.LO(Logic in Computer Science)