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: "online spatial concept and lexical acquisition with simultaneous localization and mapping"
  Abstract: In this paper, we propose an online learning algorithm based on a Rao-Blackwellized particle filter for spatial concept acquisition and mapping. We have proposed a nonparametric Bayesian spatial concept acquisition model (SpCoA). We propose a novel method (SpCoSLAM) integrating SpCoA and FastSLAM in the theoretical framework of the Bayesian generative model. The proposed method can simultaneously learn place categories and lexicons while incrementally generating an environmental map. Furthermore, the proposed method has scene image features and a language model added to SpCoA. In the experiments, we tested online learning of spatial concepts and environmental maps in a novel environment of which the robot did not have a map. Then, we evaluated the results of online learning of spatial concepts and lexical acquisition. The experimental results demonstrated that the robot was able to more accurately learn the relationships between words and the place in the environmental map incrementally by using the proposed method.

Connected through hyperedge HE-1 (induced by source paper "spatial concept based navigation with human speech instructions via probabilistic inference on bayesian generative model"):
  with members:
    - "steap simultaneous trajectory estimation and planning"
    - "from language to goals inverse reinforcement learning for vision based instruction following"
    - "reinforcement learning and control as probabilistic inference tutorial and review"
    - "visual reinforcement learning with imagined goals"
    - "improved and scalable online learning of spatial concepts and language models with mapping"
    - "vision and language navigation interpreting visually grounded navigation instructions in real environments"
    - "spatial concept acquisition for a mobile robot that integrates self localization and unsupervised word discovery from spoken sentences"
    - "symbol emergence in robotics a survey"

Connected through hyperedge HE-2 (induced by source paper "symbol emergence as an interpersonal multimodal categorization"):
  with members:
    - "emergent linguistic phenomena in multi agent communication games"
    - "serket an architecture for connecting stochastic models to realize a large scale cognitive model"
    - "emergent translation in multi agent communication"
    - "spatial concept acquisition for a mobile robot that integrates self localization and unsupervised word discovery from spoken sentences"
    - "sensorimotor input as a language generalisation tool a neurorobotics model for generation and generalisation of noun verb combinations with sensorimotor inputs"
    - "multi agent cooperation and the emergence of natural language"
    - "symbol emergence in robotics a survey"
    - "caffe convolutional architecture for fast feature embedding"

Connected through hyperedge HE-3 (induced by source paper "neuro serket development of integrative cognitive system through the composition of deep probabilistic generative models"):
  with members:
    - "cross modal variational auto encoder with distributed latent spaces and associators"
    - "multimodal generative models for scalable weakly supervised learning"
    - "deep unsupervised clustering with gaussian mixture variational autoencoders"
    - "serket an architecture for connecting stochastic models to realize a large scale cognitive model"
    - "spatial concept acquisition for a mobile robot that integrates self localization and unsupervised word discovery from spoken sentences"
    - "nonparametric bayesian double articulation analyzer for direct language acquisition from continuous speech signals"
    - "variational deep embedding an unsupervised and generative approach to clustering"
    - "variational methods for conditional multimodal deep learning"

Connected through hyperedge HE-4 (induced by source paper "symbol emergence in cognitive developmental systems a survey"):
  with members:
    - "interactive natural language acquisition in a multi modal recurrent neural architecture"
    - "interactively picking real world objects with unconstrained spoken language instructions"
    - "serket an architecture for connecting stochastic models to realize a large scale cognitive model"
    - "detection of social signals for recognizing engagement in human robot interaction"
    - "grounded language learning in a simulated 3d world"
    - "grounding spatio semantic referring expressions for human robot interaction"
    - "discovering objects and their relations from entangled scene representations"
    - "spatial concept acquisition for a mobile robot that integrates self localization and unsupervised word discovery from spoken sentences"

Connected through hyperedge HE-5 (induced by source paper "improved and scalable online learning of spatial concepts and language models with mapping"):
  with members:
    - "serket an architecture for connecting stochastic models to realize a large scale cognitive model"
    - "spatial concept acquisition for a mobile robot that integrates self localization and unsupervised word discovery from spoken sentences"
    - "place categorization and semantic mapping on a mobile robot"
    - "rao blackwellised particle filtering for dynamic bayesian networks"

Connected through hyperedge HE-6 (induced by source paper "spcoslam 2 0 an improved and scalable online learning of spatial concepts and language models with mapping"):
  with members:
    - "spatial concept acquisition for a mobile robot that integrates self localization and unsupervised word discovery from spoken sentences"
    - "place categorization and semantic mapping on a mobile robot"
    - "caffe convolutional architecture for fast feature embedding"

Connected through hyperedge HE-7 (induced by source paper "serket an architecture for connecting stochastic models to realize a large scale cognitive model"):
  with members:
    - "bayesian body schema estimation using tactile information obtained through coordinated random movements"
    - "tensorflow large scale machine learning on heterogeneous distributed systems"
    - "symbol emergence in robotics a survey"
    - "church a language for generative models"

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)