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: "building machines that learn and think for themselves commentary on lake et al behavioral and brain sciences 2017"
  Abstract: We agree with Lake and colleagues on their list of key ingredients for building humanlike intelligence, including the idea that model-based reasoning is essential. However, we favor an approach that centers on one additional ingredient: autonomy. In particular, we aim toward agents that can both build and exploit their own internal models, with minimal human hand-engineering. We believe an approach centered on autonomous learning has the greatest chance of success as we scale toward real-world complexity, tackling domains for which ready-made formal models are not available. Here we survey several important examples of the progress that has been made toward building autonomous agents with humanlike abilities, and highlight some outstanding challenges.

Connected through hyperedge HE-1 (induced by source paper "alternative techniques for mapping paths to hlai"):
  with members:
    - "forecasting transformative ai an expert survey"
    - "go explore a new approach for hard exploration problems"
    - "attention is all you need"
    - "building machines that learn and think like people"

Connected through hyperedge HE-2 (induced by source paper "measuring abstract reasoning in neural networks"):
  with members:
    - "deep learning a critical appraisal"
    - "an empirical evaluation of visual question answering for novel objects"
    - "iq of neural networks"
    - "discovering objects and their relations from entangled scene representations"
    - "measuring the tendency of cnns to learn surface statistical regularities"
    - "generalization without systematicity on the compositional skills of sequence to sequence recurrent networks"
    - "program induction by rationale generation learning to solve and explain algebraic word problems"
    - "understanding deep learning requires rethinking generalization"

Connected through hyperedge HE-3 (induced by source paper "machine theory of mind"):
  with members:
    - "pragmatic pedagogic value alignment"
    - "autonomous agents modelling other agents a comprehensive survey and open problems"
    - "robust imitation of diverse behaviors"
    - "meta learning and universality deep representations and gradient descent can approximate any learning algorithm"
    - "should robots be obedient"
    - "one shot imitation learning"
    - "deep variational information bottleneck"
    - "generative adversarial imitation learning"

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)