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: "spatial concept acquisition for a mobile robot that integrates self localization and unsupervised word discovery from spoken sentences"
  Abstract: In this paper, we propose a novel unsupervised learning method for the lexical acquisition of words related to places visited by robots, from human continuous speech signals. We address the problem of learning novel words by a robot that has no prior knowledge of these words except for a primitive acoustic model. Furthermore, we propose a method that allows a robot to effectively use the learned words and their meanings for self-localization tasks. The proposed method is nonparametric Bayesian spatial concept acquisition method (SpCoA) that integrates the generative model for self-localization and the unsupervised word segmentation in uttered sentences via latent variables related to the spatial concept. We implemented the proposed method SpCoA on SIGVerse, which is a simulation environment, and TurtleBot2, which is a mobile robot in a real environment. Further, we conducted experiments for evaluating the performance of SpCoA. The experimental results showed that SpCoA enabled the robot to acquire the names of places from speech sentences. They also revealed that the robot could effectively utilize the acquired spatial concepts and reduce the uncertainty in self-localization.

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"
    - "online spatial concept and lexical acquisition with simultaneous localization and mapping"
    - "vision and language navigation interpreting visually grounded navigation instructions in real environments"
    - "symbol emergence in robotics a survey"

Connected through hyperedge HE-2 (induced by source paper "autonomous planning based on spatial concepts to tidy up home environments with service robots"):
  with members:
    - "yolov3 an incremental improvement"
    - "multimodal sensor based semantic 3d mapping for a large scale environment"
    - "interactively picking real world objects with unconstrained spoken language instructions"
    - "orb slam2 an open source slam system for monocular stereo and rgb d cameras"
    - "cnn slam real time dense monocular slam with learned depth prediction"
    - "ssd single shot multibox detector"
    - "semanticfusion dense 3d semantic mapping with convolutional neural networks"
    - "learning deconvolution network for semantic segmentation"

Connected through hyperedge HE-3 (induced by source paper "symbol emergence as an interpersonal multimodal categorization"):
  with members:
    - "emergent linguistic phenomena in multi agent communication games"
    - "online spatial concept and lexical acquisition with simultaneous localization and mapping"
    - "serket an architecture for connecting stochastic models to realize a large scale cognitive model"
    - "emergent translation in multi agent communication"
    - "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-4 (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"
    - "online spatial concept and lexical acquisition with simultaneous localization and mapping"
    - "serket an architecture for connecting stochastic models to realize a large scale cognitive model"
    - "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-5 (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"
    - "online spatial concept and lexical acquisition with simultaneous localization and mapping"
    - "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"

Connected through hyperedge HE-6 (induced by source paper "improved and scalable online learning of spatial concepts and language models with mapping"):
  with members:
    - "online spatial concept and lexical acquisition with simultaneous localization and mapping"
    - "serket an architecture for connecting stochastic models to realize a large scale cognitive model"
    - "place categorization and semantic mapping on a mobile robot"
    - "rao blackwellised particle filtering for dynamic bayesian networks"

Connected through hyperedge HE-7 (induced by source paper "spcoslam 2 0 an improved and scalable online learning of spatial concepts and language models with mapping"):
  with members:
    - "online spatial concept and lexical acquisition with simultaneous localization and mapping"
    - "place categorization and semantic mapping on a mobile robot"
    - "caffe convolutional architecture for fast feature embedding"

Connected through hyperedge HE-8 (induced by source paper "online spatial concept and lexical acquisition with simultaneous localization and mapping"):
  with members:
    - "caffe convolutional architecture for fast feature embedding"
    - "rao blackwellised particle filtering for dynamic bayesian networks"

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)