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: "on the hardness of unlabeled multi robot motion planning"
  Abstract: In unlabeled multi-robot motion planning several interchangeable robots operate in a common workspace. The goal is to move the robots to a set of target positions such that each position will be occupied by some robot. In this paper, we study this problem for the specific case of unit-square robots moving amidst polygonal obstacles and show that it is PSPACE-hard. We also consider three additional variants of this problem and show that they are all PSPACE-hard as well. To the best of our knowledge, this is the first hardness proof for the unlabeled case. Furthermore, our proofs can be used to show that the labeled variant (where each robot is assigned with a specific target position), again, for unit-square robots, is PSPACE-hard as well, which sets another precedence, as previous hardness results require the robots to be of different shapes.

Connected through hyperedge HE-1 (induced by source paper "drrt scalable and informed asymptotically optimal multi robot motion planning"):
  with members:
    - "scalable asymptotically optimal multi robot motion planning"
    - "effective metrics for multi robot motion planning"
    - "batch informed trees bit sampling based optimal planning via the heuristically guided search of implicit random geometric graphs"
    - "motion planning for unlabeled discs with optimality guarantees"
    - "optimal sampling based motion planning under differential constraints the drift case with linear affine dynamics"
    - "efficient multi robot motion planning for unlabeled discs in simple polygons"
    - "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-2 (induced by source paper "on rearrangement of items stored in stacks"):
  with members:
    - "fast high quality dual arm rearrangement in synchronous monotone tabletop setups"
    - "efficient high quality stack rearrangement"
    - "complexity results and fast methods for optimal tabletop rearrangement with overhand grasps"
    - "pushpush and push 1 are np hard in 2d"

Connected through hyperedge HE-3 (induced by source paper "complexity of planning"):
  with members:
    - "why walking the dog takes time frechet distance has no strongly subquadratic algorithms unless seth fails"
    - "efficient multi robot motion planning for unlabeled discs in simple polygons"

Connected through hyperedge HE-4 (induced by source paper "deepmnavigate deep reinforced multi robot navigation unifying local global collision avoidance"):
  with members:
    - "densecavoid real time navigation in dense crowds using anticipatory behaviors"
    - "learning to communicate a machine learning framework for heterogeneous multi agent robotic systems"
    - "motion planning among dynamic decision making agents with deep reinforcement learning"
    - "fully distributed multi robot collision avoidance via deep reinforcement learning for safe and efficient navigation in complex scenarios"
    - "towards optimally decentralized multi robot collision avoidance via deep reinforcement learning"
    - "from perception to decision a data driven approach to end to end motion planning for autonomous ground robots"
    - "socially aware motion planning with deep reinforcement learning"
    - "uncertainty aware reinforcement learning for collision avoidance"

Connected through hyperedge HE-5 (induced by source paper "scalable centralized deep multi agent reinforcement learning via policy gradients"):
  with members:
    - "counterfactual multi agent policy gradients"
    - "magent a many agent reinforcement learning platform for artificial collective intelligence"
    - "continuous adaptation via meta learning in nonstationary and competitive environments"
    - "memory augmented control networks"
    - "curiosity driven exploration by self supervised prediction"
    - "model agnostic meta learning for fast adaptation of deep networks"
    - "cognitive mapping and planning for visual navigation"
    - "multi agent actor critic for mixed cooperative competitive environments"

Connected through hyperedge HE-6 (induced by source paper "fast high quality dual arm rearrangement in synchronous monotone tabletop setups"):
  with members:
    - "coordinating the motion of labeled discs with optimality guarantees under extreme density"
    - "scalable asymptotically optimal multi robot motion planning"
    - "complexity results and fast methods for optimal tabletop rearrangement with overhand grasps"
    - "characterizing minimum length coordinated motions for two discs"
    - "motion planning for unlabeled discs with optimality guarantees"
    - "efficient multi robot motion planning for unlabeled discs in simple polygons"
    - "asymptotically optimal algorithms for one to one pickup and delivery problems with applications to transportation systems"
    - "finding a needle in an exponential haystack discrete rrt for exploration of implicit roadmaps in multi robot motion planning"

Connected through hyperedge HE-7 (induced by source paper "coordinated motion planning reconfiguring a swarm of labeled robots with bounded stretch"):
  with members:
    - "motion planning for unlabeled discs with optimality guarantees"
    - "efficient multi robot motion planning for unlabeled discs in simple polygons"
    - "finding a needle in an exponential haystack discrete rrt for exploration of implicit roadmaps in multi robot motion planning"
    - "minimizing movement fixed parameter tractability"
    - "k color multi robot motion planning"
    - "pspace completeness of sliding block puzzles and other problems through the nondeterministic constraint logic model of computation"
    - "coin moving puzzles"

Connected through hyperedge HE-8 (induced by source paper "sear a polynomial time multi robot path planning algorithm with expected constant factor optimality guarantee"):
  with members:
    - "a portable 3d printing enabled multi vehicle platform for robotics research and education"
    - "an effective algorithmic framework for near optimal multi robot path planning"
    - "motion planning for unlabeled discs with optimality guarantees"
    - "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"

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)