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: "iterative milp methods for vehicle control problems"
  Abstract: Mixed integer linear programming (MILP) is a powerful tool for planning and control problems because of its modeling capability and the availability of good solvers. However, for large models, MILP methods suffer computationally. In this paper, we present iterative MILP algorithms that address this issue. We consider trajectory generation problems with obstacle avoidance requirements and minimum time trajectory generation problems. The algorithms use fewer binary variables than standard MILP methods and require less computational effort.

Connected through hyperedge HE-1 (induced by source paper "collision free navigation of a multi robot team for intruder interception"):
  with members:
    - "dynamic coverage of mobile sensor networks"

Connected through hyperedge HE-2 (induced by source paper "average case constant factor time and distance optimal multi robot path planning in well connected environments"):
  with members:
    - "lifelong multi agent path finding for online pickup and delivery tasks"
    - "sear a polynomial time expected constant factor optimal algorithmic framework for multi robot path planning"
    - "motion planning for unlabeled discs with optimality guarantees"
    - "on the hardness of unlabeled multi robot motion planning"
    - "efficient multi robot motion planning for unlabeled discs in simple polygons"
    - "a linear time algorithm for the feasibility of pebble motion on graphs"
    - "k color multi robot motion planning"
    - "distance optimal formation control on graphs with a tight convergence time guarantee"

Connected through hyperedge HE-3 (induced by source paper "conservative collision prediction and avoidance for stochastic trajectories in continuous time and space"):
  with members:
    - "chance constrained model predictive control for multi agent systems"

Connected through hyperedge HE-4 (induced by source paper "resource driven mission phasing techniques for constrained agents in stochastic environments"):
  with members:
    - "flexible decomposition algorithms for weakly coupled markov decision problems"
    - "the complexity of decentralized control of markov decision processes"
    - "resource allocation among agents with mdp induced preferences"
    - "decentralized control of cooperative systems categorization and complexity analysis"
    - "efficient solution algorithms for factored mdps"
    - "multiagent control of self reconfigurable robots"
    - "decision theoretic planning structural assumptions and computational leverage"

Connected through hyperedge HE-5 (induced by source paper "a decomposition approach to multi vehicle cooperative control"):
  with members:
    - "multi vehicle cooperative control using mixed integer linear programming"

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)