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: "serket an architecture for connecting stochastic models to realize a large scale cognitive model"
  Abstract: To realize human-like robot intelligence, a large-scale cognitive architecture is required for robots to understand the environment through a variety of sensors with which they are equipped. In this paper, we propose a novel framework named Serket that enables the construction of a large-scale generative model and its inference easily by connecting sub-modules to allow the robots to acquire various capabilities through interaction with their environments and others. We consider that large-scale cognitive models can be constructed by connecting smaller fundamental models hierarchically while maintaining their programmatic independence. Moreover, connected modules are dependent on each other, and parameters are required to be optimized as a whole. Conventionally, the equations for parameter estimation have to be derived and implemented depending on the models. However, it becomes harder to derive and implement those of a larger scale model. To solve these problems, in this paper, we propose a method for parameter estimation by communicating the minimal parameters between various modules while maintaining their programmatic independence. Therefore, Serket makes it easy to construct large-scale models and estimate their parameters via the connection of modules. Experimental results demonstrated that the model can be constructed by connecting modules, the parameters can be optimized as a whole, and they are comparable with the original models that we have proposed.

Connected through hyperedge HE-1 (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"
    - "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-2 (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"
    - "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-3 (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"
    - "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-4 (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"
    - "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"

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)