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: "social groups and pedestrian crowds experiment on dyads in a counter flow scenario"
  Abstract: The calibration and validation of pedestrian simulations require the acquisition of empirical evidences of human behaviour. The current work presents the results of an experiment focused on the potentially combined effect of counter flow and grouping on pedestrian dynamics. In particular, we focused on: (i) four different configurations of flow ratio (the rate between the minor flow and the total flow in bidirectional scenarios); (ii) dyads, as the most frequently observed and basic social groups of crowds. Results showed that the increase of flow ratio negatively impacted the speed of pedestrians. Dyads walked significantly slower than singletons, due to the difficulty in movement coordination among group members (proxemics) in case of counter flow. The collected results represent an useful contribution towards the validation of pedestrian simulations.

Connected through hyperedge HE-1 (induced by source paper "micro and macro pedestrian dynamics in counterflow the impact of social groups"):
  with members:
    - "investigating the effect of social groups in uni directional pedestrian flow"
    - "towards an integrated approach to crowd analysis and crowd synthesis"

Connected through hyperedge HE-2 (induced by source paper "investigating the effect of social groups in uni directional pedestrian flow"):
  with members:
    - "micro and macro pedestrian dynamics in counterflow the impact of social groups"

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.MA(Multiagent Systems)