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: "distance optimal formation control on graphs with a tight convergence time guarantee"
  Abstract: For the task of moving a set of indistinguishable agents on a connected graph with unit edge distance to an arbitrary set of goal vertices, free of collisions, we propose a fast distance optimal control algorithm that guides the agents into the desired formation. Moreover, we show that the algorithm also provides a tight convergence time guarantee (time optimality and distance optimality cannot be simultaneously satisfied). Our generic graph formulation allows the algorithm to be applied to scenarios such as grids with holes (modeling obstacles) in arbitrary dimensions. Simulations, available online, confirm our theoretical developments.

Connected through hyperedge HE-1 (induced by source paper "ddm fast near optimal multi robot path planning using diversified path and optimal sub problem solution database heuristics"):
  with members:
    - "multi agent pathfinding definitions variants and benchmarks"
    - "priority inheritance with backtracking for iterative multi agent path finding"
    - "automatic algorithm selection in multi agent pathfinding"
    - "coordinating the motion of labeled discs with optimality guarantees under extreme density"
    - "x anytime multiagent planning with bounded search"
    - "constant factor time optimal multi robot routing on high dimensional grids in mostly sub quadratic time"
    - "lifelong multi agent path finding for online pickup and delivery tasks"
    - "learning the problem optimum map analysis and application to global optimization in robotics"

Connected through hyperedge HE-2 (induced by source paper "learning safe unlabeled multi robot planning with motion constraints"):
  with members:
    - "impala scalable distributed deep rl with importance weighted actor learner architectures"
    - "scalable centralized deep multi agent reinforcement learning via policy gradients"
    - "distributed prioritized experience replay"
    - "counterfactual multi agent policy gradients"
    - "rllib abstractions for distributed reinforcement learning"
    - "proximal policy optimization algorithms"
    - "multi agent actor critic for mixed cooperative competitive environments"
    - "semi supervised classification with graph convolutional networks"

Connected through hyperedge HE-3 (induced by source paper "graph policy gradients for large scale unlabeled motion planning with constraints"):
  with members:
    - "stability of graph scattering transforms"
    - "learning safe unlabeled multi robot planning with motion constraints"
    - "graph policy gradients for large scale robot control"
    - "a comprehensive survey on graph neural networks"
    - "learning sample efficient target reaching for mobile robots"
    - "semi supervised classification with graph convolutional networks"

Connected through hyperedge HE-4 (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"
    - "multi agent path planning and network flow"

Connected through hyperedge HE-5 (induced by source paper "sear a polynomial time expected constant factor optimal algorithmic framework for multi robot path planning"):
  with members:
    - "a portable 3d printing enabled multi vehicle platform for robotics research and education"
    - "on the hardness of unlabeled multi robot motion planning"
    - "a linear time algorithm for the feasibility of pebble motion on graphs"
    - "finding a needle in an exponential haystack discrete rrt for exploration of implicit roadmaps in multi robot motion planning"
    - "k color multi robot motion planning"

Connected through hyperedge HE-6 (induced by source paper "motion planning for unlabeled discs with optimality guarantees"):
  with members:
    - "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"
    - "finding a needle in an exponential haystack discrete rrt for exploration of implicit roadmaps in multi robot motion planning"
    - "k color multi robot motion planning"
    - "multi agent path planning and network flow"
    - "planning optimal paths for multiple robots on graphs"
    - "on the power of manifold samples in exploring configuration spaces and the dimensionality of narrow passages"

Connected through hyperedge HE-7 (induced by source paper "efficient multi robot motion planning for unlabeled discs in simple polygons"):
  with members:
    - "motion planning for unlabeled discs with optimality guarantees"
    - "on the hardness of unlabeled multi robot motion planning"
    - "finding a needle in an exponential haystack discrete rrt for exploration of implicit roadmaps in multi robot motion planning"
    - "k color multi robot motion planning"
    - "on the power of manifold samples in exploring configuration spaces and the dimensionality of narrow passages"
    - "pspace completeness of sliding block puzzles and other problems through the nondeterministic constraint logic model of computation"
    - "algorithms for rapidly dispersing robot swarms in unknown environments"

Connected through hyperedge HE-8 (induced by source paper "target assignment in robotic networks distance optimality guarantees and hierarchical strategies"):
  with members:
    - "asymptotically optimal algorithms for one to one pickup and delivery problems with applications to transportation systems"
    - "fundamentals of large sensor networks connectivity capacity clocks and computation"

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)