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: "privacy verification in pomdps via barrier certificates"
  Abstract: Privacy is an increasing concern in cyber-physical systems that operates over a shared network. In this paper, we propose a method for privacy verification of cyber- physical systems modeled by Markov decision processes (MDPs) and partially-observable Markov decision processes (POMDPs) based on barrier certificates. To this end, we consider an opacity-based notion of privacy, which is characterized by the beliefs in system states. We show that the belief update equations can be represented as discrete-time switched systems, for which we propose a set of conditions for privacy verification in terms of barrier certificates. We further demonstrate that, for MDPs and for POMDPs, privacy verification can be computationally implemented by solving a set of semi-definite programs and sum-of-squares programs, respectively. The method is illustrated by an application to privacy verification of an inventory management system.

Connected through hyperedge HE-1 (induced by source paper "control theory meets pomdps a hybrid systems approach"):
  with members:
    - "safe policy synthesis in multi agent pomdps via discrete time barrier functions"
    - "verification of uncertain pomdps using barrier certificates"
    - "understanding the role of adaptivity in machine teaching the case of version space learners"
    - "barrier certificates for assured machine teaching"
    - "machine teaching a new paradigm for building machine learning systems"
    - "safe learning of regions of attraction for uncertain nonlinear systems with gaussian processes"
    - "heuristic search value iteration for pomdps"
    - "control of probabilistic systems under dynamic partially known environments with temporal logic specifications"

Connected through hyperedge HE-2 (induced by source paper "safe policy synthesis in multi agent pomdps via discrete time barrier functions"):
  with members:
    - "verification of uncertain pomdps using barrier certificates"
    - "barrier certificates for assured machine teaching"
    - "shielded decision making in mdps"
    - "enhancing the performance of a safe controller via supervised learning for truck lateral control"
    - "the communicative multiagent team decision problem analyzing teamwork theories and models"

Connected through hyperedge HE-3 (induced by source paper "verification of uncertain pomdps using barrier certificates"):
  with members:
    - "a storm is coming a modern probabilistic model checker"
    - "a berkeley view of systems challenges for ai"
    - "concrete problems in ai safety"
    - "research priorities for robust and beneficial artificial intelligence"
    - "heuristic search value iteration for pomdps"
    - "control of probabilistic systems under dynamic partially known environments with temporal logic specifications"
    - "perseus randomized point based value iteration for pomdps"
    - "value function approximations for partially observable markov decision processes"

Connected through hyperedge HE-4 (induced by source paper "barrier certificates for assured machine teaching"):
  with members:
    - "verification of uncertain pomdps using barrier certificates"
    - "an optimal control approach to sequential machine teaching"
    - "understanding the role of adaptivity in machine teaching the case of version space learners"
    - "machine teaching a new paradigm for building machine learning systems"
    - "preference based teaching"

Connected through hyperedge HE-5 (induced by source paper "cost bounded active classification using partially observable markov decision processes"):
  with members:
    - "barrier certificates for assured machine teaching"
    - "bounded policy synthesis for pomdps with safe reachability objectives"
    - "pomdp model learning for human robot collaboration"
    - "synthesis of surveillance strategies via belief abstraction"
    - "active classification theory and application to underwater inspection"

Connected through hyperedge HE-6 (induced by source paper "pomdp model learning for human robot collaboration"):
  with members:
    - "verification of uncertain pomdps using barrier certificates"
    - "a learning based optimal human robot collaboration with linear temporal logic constraints"
    - "efficient model learning from joint action demonstrations for human robot collaborative tasks"
    - "qualitative analysis of pomdps with temporal logic specifications for robotics applications"
    - "probably approximately correct mdp learning and control with temporal logic constraints"

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)