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: "robot planning with mathematical models of human state and action"
  Abstract: Robots interacting with the physical world plan with models of physics. We advocate that robots interacting with people need to plan with models of cognition. This writeup summarizes the insights we have gained in integrating computational cognitive models of people into robotics planning and control. It starts from a general game-theoretic formulation of interaction, and analyzes how different approximations result in different useful coordination behaviors for the robot during its interaction with people.

Connected through hyperedge HE-1 (induced by source paper "active reinforcement learning with monte carlo tree search"):
  with members:
    - "deep tamer interactive agent shaping in high dimensional state spaces"
    - "trial without error towards safe reinforcement learning via human intervention"
    - "thinking fast and slow with deep learning and tree search"
    - "generative adversarial imitation learning"
    - "benchmarking for bayesian reinforcement learning"
    - "bayesian reinforcement learning a survey"
    - "algorithms for multi armed bandit problems"
    - "near optimal brl using optimistic local transitions"

Connected through hyperedge HE-2 (induced by source paper "explicability legibility predictability transparency privacy security the emerging landscape of interpretable agent behavior"):
  with members:
    - "planning with explanatory actions a joint approach to plan explicability and explanations in human aware planning"
    - "expressing robot incapability"
    - "towards providing explanations for ai planner decisions"
    - "generating plans that predict themselves"
    - "algorithms for the greater good on mental modeling and acceptable symbiosis in human ai collaboration"
    - "ai challenges in human robot cognitive teaming"

Connected through hyperedge HE-3 (induced by source paper "incomplete contracting and ai alignment"):
  with members:
    - "inverse reward design"
    - "equality of opportunity in supervised learning"
    - "cooperative inverse reinforcement learning"
    - "concrete problems in ai safety"
    - "inherent trade offs in the fair determination of risk scores"
    - "the off switch game"

Connected through hyperedge HE-4 (induced by source paper "finding plans subject to stipulations on what information they divulge"):
  with members:
    - "complete characterization of a class of privacy preserving tracking problems"

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)