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: "persistent monitoring of events with stochastic arrivals at multiple stations"
  Abstract: This paper introduces a new mobile sensor scheduling problem, involving a single robot tasked with monitoring several events of interest that occur at different locations. Of particular interest is the monitoring of transient events that can not be easily forecast. Application areas range from natural phenomena ({\em e.g.}, monitoring abnormal seismic activity around a volcano using a ground robot) to urban activities ({\em e.g.}, monitoring early formations of traffic congestion using an aerial robot). Motivated by those and many other examples, this paper focuses on problems in which the precise occurrence times of the events are unknown {\em a priori}, but statistics for their inter-arrival times are available. The robot's task is to monitor the events to optimize the following two objectives: {\em (i)} maximize the number of events observed and {\em (ii)} minimize the delay between two consecutive observations of events occurring at the same location. The paper considers the case when a robot is tasked with optimizing the event observations in a balanced manner, following a cyclic patrolling route. First, assuming the cyclic ordering of stations is known, we prove the existence and uniqueness of the optimal solution, and show that the optimal solution has desirable convergence and robustness properties. Our constructive proof also produces an efficient algorithm for computing the unique optimal solution with $O(n)$ time complexity, in which $n$ is the number of stations, with $O(\log n)$ time complexity for incrementally adding or removing stations. Except for the algorithm, most of the analysis remains valid when the cyclic order is unknown. We then provide a polynomial-time approximation scheme that gives a $(1+\epsilon)$-optimal solution for this more general, NP-hard problem.

Connected through hyperedge HE-1 (induced by source paper "sampling based incremental information gathering with applications to robotic exploration and environmental monitoring"):
  with members:
    - "warped gaussian processes occupancy mapping with uncertain inputs"
    - "gaussian process autonomous mapping and exploration for range sensing mobile robots"
    - "sampling based algorithms for optimal motion planning"
    - "efficient informative sensing using multiple robots"

Connected through hyperedge HE-2 (induced by source paper "a sub modular receding horizon solution for mobile multi agent persistent monitoring"):
  with members:
    - "multi robot routing for persistent monitoring with latency constraints"
    - "combinatorial algorithms for control of biological regulatory networks"
    - "distributed submodular maximization with limited information"
    - "a supermodular optimization framework for leader selection under link noise in linear multi agent systems"

Connected through hyperedge HE-3 (induced by source paper "a hybrid approach to persistent coverage in stochastic environments"):
  with members:
    - "persistent robotic tasks monitoring and sweeping in changing environments"
    - "dynamic coverage of mobile sensor networks"

Connected through hyperedge HE-4 (induced by source paper "on sensing agility and computation requirements for a data gathering agile robotic vehicle"):
  with members:
    - "uncertainty in monotone co design problems"
    - "persistent monitoring in discrete environments minimizing the maximum weighted latency between observations"
    - "persistent robotic tasks monitoring and sweeping in changing environments"
    - "an optimal control approach for the persistent monitoring problem"

Connected through hyperedge HE-5 (induced by source paper "algorithms for visibility based monitoring with robot teams"):
  with members:
    - "persistent monitoring in discrete environments minimizing the maximum weighted latency between observations"
    - "persistent robotic tasks monitoring and sweeping in changing environments"

Connected through hyperedge HE-6 (induced by source paper "correlated orienteering problem and it application to persistent monitoring tasks"):
  with members:
    - "memoryless control design for persistent surveillance under safety constraints"
    - "persistent monitoring in discrete environments minimizing the maximum weighted latency between observations"
    - "persistent robotic tasks monitoring and sweeping in changing environments"
    - "sampling based algorithms for optimal motion planning"

Connected through hyperedge HE-7 (induced by source paper "optimal tourist problem and anytime planning of trip itineraries"):
  with members:
    - "persistent monitoring in discrete environments minimizing the maximum weighted latency between observations"
    - "persistent robotic tasks monitoring and sweeping in changing environments"
    - "sampling based algorithms for optimal motion planning"

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.RO(Robotics)