human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "tackling existence probabilities of objects with motion planning for automated urban driving"):
  Abstract: Motion planners take uncertain information about the environment as an input. The environment information is most of the time noisy and has a tendency to contain false positive object detections, rather than false negatives. The state-of-the art motion planning approaches take uncertain state and prediction of objects into account, but fail to distinguish between their existence probabilities. #R##N#In this paper we present a planning approach that considers the existence probabilities of objects. The proposed approach reacts to falsely detected phantom objects smoothly, and in this way tolerates the faults arising from perception and prediction without performing harsh reactions, unless such reactions are unavoidable for maintaining safety.

Includes members:
  Member "behavior planning of autonomous cars with social perception":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "cmetric a driving behavior measure using centrality functions")
  Member "occlusion aware risk assessment for autonomous driving in urban environments":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "behavior planning of autonomous cars with social perception")
  Member "tackling occlusions limited sensor range with set based safety verification":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "behavior planning of autonomous cars with social perception")
  Member "limited visibility and uncertainty aware motion planning for automated driving":
    also connected through other hyperedges:
      (none)
  Member "on a formal model of safe and scalable self driving cars":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "training adversarial agents to exploit weaknesses in deep control policies")
  Member "find your own way weakly supervised segmentation of path proposals for urban autonomy":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "learning a directional soft lane affordance model for road scenes using self supervision")

Question: Please tell me which class the source paper 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)