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 "conflict based force aggregation"):
  Abstract: In this paper we present an application where we put together two methods for clustering and classification into a force aggregation method. Both methods are based on conflicts between elements. These methods work with different type of elements (intelligence reports, vehicles, military units) on different hierarchical levels using specific conflict assessment methods on each level. We use Dempster-Shafer theory for conflict calculation between elements, Dempster-Shafer clustering for clustering these elements, and templates for classification. The result of these processes is a complete force aggregation on all levels handled.

Includes members:
  Member "finding a posterior domain probability distribution by specifying nonspecific evidence":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "managing inconsistent intelligence")
  Member "a neural network and iterative optimization hybrid for dempster shafer clustering":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "managing inconsistent intelligence")
  Member "on nonspecific evidence":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "managing inconsistent intelligence")
  Member "managing inconsistent intelligence":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "robust report level cluster to track fusion")
  Member "creating prototypes for fast classification in dempster shafer clustering":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "managing inconsistent intelligence")
  Member "specifying nonspecific evidence":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "managing inconsistent intelligence")
  Member "fast dempster shafer clustering using a neural network structure":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "managing inconsistent intelligence")
  Member "simultaneous dempster shafer clustering and gradual determination of number of clusters using a neural network structure":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "managing inconsistent intelligence")

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.AI(Artificial Intelligence)