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: "stigmergy based modeling to discover urban activity patterns from positioning data"
  Abstract: Positioning data offer a remarkable source of information to analyze crowds urban dynamics. However, discovering urban activity patterns from the emergent behavior of crowds involves complex system modeling. An alternative approach is to adopt computational techniques belonging to the emergent paradigm, which enables self-organization of data and allows adaptive analysis. Specifically, our approach is based on stigmergy. By using stigmergy each sample position is associated with a digital pheromone deposit, which progressively evaporates and aggregates with other deposits according to their spatiotemporal proximity. Based on this principle, we exploit positioning data to identify high-density areas (hotspots) and characterize their activity over time. This characterization allows the comparison of dynamics occurring in different days, providing a similarity measure exploitable by clustering techniques. Thus, we cluster days according to their activity behavior, discovering unexpected urban activity patterns. As a case study, we analyze taxi traces in New York City during 2015.

Connected through hyperedge HE-1 (induced by source paper "assessing refugees integration via spatio temporal similarities of mobility and calling behaviors"):
  with members:
    - "detecting permanent and intermittent purchase hotspots via computational stigmergy"
    - "data for refugees the d4r challenge on mobility of syrian refugees in turkey"
    - "a stigmergy based analysis of city hotspots to discover trends and anomalies in urban transportation usage"
    - "studying migrant assimilation through facebook interests"
    - "spatio temporal data mining a survey of problems and methods"
    - "crisis analytics big data driven crisis response"
    - "mobile communication signatures of unemployment"
    - "an analytical framework to nowcast well being using mobile phone data"

Connected through hyperedge HE-2 (induced by source paper "stigmergic independent reinforcement learning for multi agent collaboration"):
  with members:
    - "deep reinforcement learning a brief survey"
    - "accnet actor coordinator critic net for learning to communicate with deep multi agent reinforcement learning"
    - "learning to communicate with deep multi agent reinforcement learning"
    - "prioritized experience replay"
    - "mobile crowd sensing and computing when participatory sensing meets participatory social media"
    - "the arcade learning environment an evaluation platform for general agents"
    - "antnet distributed stigmergetic control for communications networks"

Connected through hyperedge HE-3 (induced by source paper "detecting permanent and intermittent purchase hotspots via computational stigmergy"):
  with members:
    - "a stigmergy based analysis of city hotspots to discover trends and anomalies in urban transportation usage"
    - "spatio temporal sentiment hotspot detection using geotagged photos"

Connected through hyperedge HE-4 (induced by source paper "a stigmergy based analysis of city hotspots to discover trends and anomalies in urban transportation usage"):
  with members:
    - "an adaptive stigmergy based system for evaluating technological indicator dynamics in the context of smart specialization"

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)