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: "a physically based particle model of emergent crowd behaviors"
  Abstract: This paper presents a modeling process in order to produce a realistic simulation of crowds in the ancient Greek agora of Argos. This place was a social theater in which two kinds of collective phenomena took place: interpersonal interactions (small group discussion and negotiation, etc.) and global collective phenomena, such as flowing and jamming. In this paper, we focus on the second type of collective human phenomena, called non-deliberative emergent crowd phenomena. This is a typical case of collective emergent self-organization. When a great number of individuals move within a confined environment and under a common fate, collective structures appear spontaneously: jamming with inner collapses, organized flowing with queues, curls, and vortices, propagation effects, etc. These are particularly relevant features to enhance the realism - more precisely the "truthfulness" - of models of this kind of collective phenomena. We assume that this truthfulness is strongly associated with the concept of emergence: evolutions are not predetermined by the individual characters, but emerge from the interaction of numerous characters. The evolutions are not repetitive, and evolve on the basis of small changes. This paper demonstrates that the physically-based interacting particles system is an adequate candidate to model emergent crowd effects: it associates a large number of elementary dynamic actors via elementary non-linear dynamic interactions. Our model of the scene is regulated as a large, dynamically coupled network of second order differential automata. We take advantage of symbolic non-photorealistic and efficient visualization to render the style of the person, rather than the person itself. As an artistic representation, NPR reinforces the symbolic acceptance of the scene by the observer, triggering an immediate and intuitive recognition of the scene as a plausible scene from ancient Greece.

Connected through hyperedge HE-1 (induced by source paper "social behavior learning with realistic reward shaping"):
  with members:
    - "the limits and potentials of deep learning for robotics"
    - "autonomous driving in reality with reinforcement learning and image translation"
    - "unity a general platform for intelligent agents"
    - "using simulation and domain adaptation to improve efficiency of deep robotic grasping"
    - "deep reinforcement learning that matters"
    - "robot gains social intelligence through multimodal deep reinforcement learning"
    - "proximal policy optimization algorithms"
    - "learning to navigate in complex environments"

Connected through hyperedge HE-2 (induced by source paper "learning socially appropriate robot approaching behavior toward groups using deep reinforcement learning"):
  with members:
    - "the limits and potentials of deep learning for robotics"
    - "autonomous driving in reality with reinforcement learning and image translation"
    - "unity a general platform for intelligent agents"
    - "using simulation and domain adaptation to improve efficiency of deep robotic grasping"
    - "deep reinforcement learning that matters"
    - "robot gains social intelligence through multimodal deep reinforcement learning"
    - "proximal policy optimization algorithms"
    - "learning to navigate in complex environments"

Connected through hyperedge HE-3 (induced by source paper "building exploration with leeches hirudo verbana"):
  with members:
    - "on exploration of geometrically constrained space by medicinal leeches hirudo verbana"

Connected through hyperedge HE-4 (induced by source paper "towards a serious games evacuation simulator"):
  with members:
    - "microscopic pedestrian flow characteristics development of an image processing data collection and simulation model"
    - "crowd simulation modeling applied to emergency and evacuation simulations using multi agent systems"

Connected through hyperedge HE-5 (induced by source paper "using serious games to train evacuation behaviour"):
  with members:
    - "crowd simulation modeling applied to emergency and evacuation simulations using multi agent systems"

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.GR(Graphics)