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: "reasoning about beliefs and actions under computational resource constraints"
  Abstract: Although many investigators affirm a desire to build reasoning systems that behave consistently with the axiomatic basis defined by probability theory and utility theory, limited resources for engineering and computation can make a complete normative analysis impossible. We attempt to move discussion beyond the debate over the scope of problems that can be handled effectively to cases where it is clear that there are insufficient computational resources to perform an analysis deemed as complete. Under these conditions, we stress the importance of considering the expected costs and benefits of applying alternative approximation procedures and heuristics for computation and knowledge acquisition. We discuss how knowledge about the structure of user utility can be used to control value tradeoffs for tailoring inference to alternative contexts. We address the notion of real-time rationality, focusing on the application of knowledge about the expected timewise-refinement abilities of reasoning strategies to balance the benefits of additional computation with the costs of acting with a partial result. We discuss the benefits of applying decision theory to control the solution of difficult problems given limitations and uncertainty in reasoning resources.

Connected through hyperedge HE-1 (induced by source paper "flexible deep neural network processing"):
  with members:
    - "in datacenter performance analysis of a tensor processing unit"
    - "chexnet radiologist level pneumonia detection on chest x rays with deep learning"
    - "end to end learning for self driving cars"
    - "deep residual learning for image recognition"
    - "caffe convolutional architecture for fast feature embedding"
    - "time dependent utility and action under uncertainty"

Connected through hyperedge HE-2 (induced by source paper "interruptible algorithms for multiproblem solving"):
  with members:
    - "further connections between contract scheduling and ray searching problems"
    - "new techniques for algorithm portfolio design"

Connected through hyperedge HE-3 (induced by source paper "anytime neural networks via joint optimization of auxiliary losses"):
  with members:
    - "skipnet learning dynamic routing in convolutional networks"
    - "convolutional networks with adaptive inference graphs"
    - "squeezenet alexnet level accuracy with 50x fewer parameters and 0 5mb model size"
    - "aggregated residual transformations for deep neural networks"
    - "cross stitch networks for multi task learning"
    - "inception v4 inception resnet and the impact of residual connections on learning"
    - "densely connected convolutional networks"
    - "wide residual networks"

Connected through hyperedge HE-4 (induced by source paper "learning model based planning from scratch"):
  with members:
    - "metacontrol for adaptive imagination based optimization"
    - "deep visual foresight for planning robot motion"
    - "adaptive computation time for recurrent neural networks"
    - "the predictron end to end learning and planning"
    - "strategic attentive writer for learning macro actions"
    - "value iteration networks"
    - "conditional computation in neural networks for faster models"
    - "embed to control a locally linear latent dynamics model for control from raw images"

Connected through hyperedge HE-5 (induced by source paper "research priorities for robust and beneficial artificial intelligence"):
  with members:
    - "toward idealized decision theory"
    - "friendly artificial intelligence the physics challenge"
    - "practical verification of decision making in agent based autonomous systems"
    - "decision theory with resource bounded agents"
    - "game theory with translucent players"
    - "quasi newton methods a new direction"
    - "i don t want to think about it now decision theory with costly computation"
    - "provably bounded optimal agents"

Connected through hyperedge HE-6 (induced by source paper "metareasoning for planning under uncertainty"):
  with members:
    - "selecting computations theory and applications"
    - "reasoning metareasoning and mathematical truth studies of theorem proving under limited resources"
    - "a bayesian approach to tackling hard computational problems"
    - "ideal reformulation of belief networks"

Connected through hyperedge HE-7 (induced by source paper "algorithmic rationality game theory with costly computation"):
  with members:
    - "i don t want to think about it now decision theory with costly computation"
    - "game theory with costly computation"
    - "extensive games with possibly unaware players"

Connected through hyperedge HE-8 (induced by source paper "sequential equilibrium in computational games"):
  with members:
    - "algorithmic rationality game theory with costly computation"
    - "i don t want to think about it now decision theory with costly computation"

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)