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: "planning with explanatory actions a joint approach to plan explicability and explanations in human aware planning"
  Abstract: In this work, we formulate the process of generating explanations as model reconciliation for planning problems as one of planning with explanatory actions. We show that these problems could be better understood within the framework of epistemic planning and that, in fact, most earlier works on explanation as model reconciliation correspond to tractable subsets of epistemic planning problems. We empirically show how our approach is computationally more efficient than existing techniques for explanation generation and we end the paper with a discussion of how this formulation could be extended to generate novel explanatory behaviors.

Connected through hyperedge HE-1 (induced by source paper "challenges of human aware ai systems"):
  with members:
    - "explicability legibility predictability transparency privacy security the emerging landscape of interpretable agent behavior"
    - "plan explanations as model reconciliation an empirical study"
    - "a unified framework for planning in adversarial and cooperative environments"
    - "recognizing plans by learning embeddings from observed action distributions"
    - "ai challenges in human robot cognitive teaming"
    - "plan explanations as model reconciliation moving beyond explanation as soliloquy"
    - "discovering underlying plans based on distributed representations of actions"
    - "plan explicability and predictability for robot task planning"

Connected through hyperedge HE-2 (induced by source paper "explicability legibility predictability transparency privacy security the emerging landscape of interpretable agent behavior"):
  with members:
    - "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"
    - "robot planning with mathematical models of human state and action"

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.AI(Artificial Intelligence)