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 "highly parallelized data driven mpc for minimal intervention shared control"):
  Abstract: We present a shared control paradigm that improves a user's ability to operate complex, dynamic systems in potentially dangerous environments without a priori knowledge of the user's objective. In this paradigm, the role of the autonomous partner is to improve the general safety of the system without constraining the user's ability to achieve unspecified behaviors. Our approach relies on a data-driven, model-based representation of the joint human-machine system to evaluate, in parallel, a significant number of potential inputs that the user may wish to provide. These samples are used to (1) predict the safety of the system over a receding horizon, and (2) minimize the influence of the autonomous partner. The resulting shared control algorithm maximizes the authority allocated to the human partner to improve their sense of agency, while improving safety. We evaluate the efficacy of our shared control algorithm with a human subjects study (n=20) conducted in two simulated environments: a balance bot and a race car. During the experiment, users are free to operate each system however they would like (i.e., there is no specified task) and are only asked to try to avoid unsafe regions of the state space. Using modern computational resources (i.e., GPUs) our approach is able to consider more than 10,000 potential trajectories at each time step in a control loop running at 100Hz for the balance bot and 60Hz for the race car. The results of the study show that our shared control paradigm improves system safety without knowledge of the user's goal, while maintaining high-levels of user satisfaction and low-levels of frustration. Our code is available online at this https URL.

Includes members:
  Member "operation and imitation under safety aware shared control":
    also connected through other hyperedges:
      (none)
  Member "learning models for shared control of human machine systems with unknown dynamics":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "active learning of dynamics for data driven control using koopman operators")
  Member "shared autonomy via deep reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "real world human robot collaborative reinforcement learning")
  Member "on infusing reachability based safety assurance within probabilistic planning frameworks for human robot vehicle interactions":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "universally safe swerve manoeuvres for autonomous driving")
  Member "bridging the gap between safety and real time performance in receding horizon trajectory design for mobile robots":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "reachable sets for safe real time manipulator trajectory design")
  Member "shared autonomy via hindsight optimization for teleoperation and teaming":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a general arbitration model for robust human robot shared control with multi source uncertainty modeling")
  Member "safe trajectory synthesis for autonomous driving in unforeseen environments":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "towards provably not at fault control of autonomous robots in arbitrary dynamic environments")
  Member "model based control using koopman operators":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "koopman based control of a soft continuum manipulator under variable loading conditions")

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)