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 "cooperation aware lane change maneuver in dense traffic based on model predictive control with recurrent neural network"):
  Abstract: This paper presents a real-time lane change control framework of autonomous driving in dense traffic, which exploits cooperative behaviors of other drivers. This paper focuses on heavy traffic where vehicles cannot change lanes without cooperating with other drivers. In this case, classical robust controls may not apply since there is no safe area to merge to without interacting with the other drivers. That said, modeling complex and interactive human behaviors is highly non-trivial from the perspective of control engineers. We propose a mathematical control framework based on Model Predictive Control (MPC) encompassing a state-of-the-art Recurrent Neural network (RNN) architecture. In particular, RNN predicts interactive motions of other drivers in response to potential actions of the autonomous vehicle, which are then systematically evaluated in safety constraints. We also propose a real-time heuristic algorithm to find locally optimal control inputs. Finally, quantitative and qualitative analysis on simulation studies are presented to illustrate the benefits of the proposed framework.

Includes members:
  Member "drogon a causal reasoning framework for future trajectory forecast":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a novel graph based trajectory predictor with pseudo oracle")
  Member "interaction aware decision making with adaptive strategies under merging scenarios":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "driving in dense traffic with model free reinforcement learning")
  Member "cooperation aware reinforcement learning for merging in dense traffic":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "survey of deep reinforcement learning for motion planning of autonomous vehicles")
  Member "real time ecological velocity planning for plug in hybrid vehicles with partial communication to traffic lights":
    also connected through other hyperedges:
      (none)
  Member "safe reinforcement learning on autonomous vehicles":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "interactive decision making for autonomous vehicles in dense traffic")
  Member "driving in dense traffic with model free reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "survey of deep reinforcement learning for motion planning of autonomous vehicles")
  Member "design and implementation of ecological adaptive cruise control for autonomous driving with communication to traffic lights":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "real time ecological velocity planning for plug in hybrid vehicles with partial communication to traffic lights")
  Member "social gan socially acceptable trajectories with generative adversarial networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "dlow diversifying latent flows for diverse human motion prediction")

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)