human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "pedestrian route choice by iterated equilibrium search"):
  Abstract: In vehicular traffic planning it is a long standing problem how to assign demand such on the available model of a road network that an equilibrium with regard to travel time or generalized costs is realized. For pedestrian traffic this question can be asked as well. However, as the infrastructure of pedestrian dynamics is not a network (a graph), but two-dimensional, there is in principle an infinitely large set of routes. As a consequence none of the iterating assignment methods developed for road traffic can be applied for pedestrians. In this contribution a method to overcome this problem is briefly summarized and applied with an example geometry which as a result is enhanced with routes with intermediate destination areas of certain shape. The enhanced geometry is used in some exemplary assignment calculations.

Includes members:
  Member "dynamic assignment in microsimulations of pedestrians":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "how to apply assignment methods that were developed for vehicular traffic to pedestrian microsimulations")
  Member "modelling dynamic route choice of pedestrians to assess the criticality of building evacuation":
    also connected through other hyperedges:
      (none)
  Member "the use of dynamic distance potential fields for pedestrian flow around corners":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "extended range telepresence for evacuation training in pedestrian simulations")
  Member "pedestrian flow at bottlenecks validation and calibration of vissim s social force model of pedestrian traffic and its empirical foundations":
    also connected through other hyperedges:
      (none)

Question: Please tell me which class the source paper 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)