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 "disarm a social distributed agent reputation model based on defeasible logic"):
  Abstract: Intelligent Agents act in open and thus risky environments, hence making the appropriate decision about who to trust in order to interact with, could be a challenging process. As intelligent agents are gradually enriched with Semantic Web technology, acting on behalf of their users with limited or no human intervention, their ability to perform assigned tasks is scrutinized. Hence, trust and reputation models, based on interaction trust or witness reputation, have been proposed, yet they often presuppose the use of a centralized authority. Although such mechanisms are more popular, they are usually faced with skepticism, since users may question the trustworthiness and the robustness of a central authority. Distributed models, on the other hand, are more complex but they provide personalized estimations based on each agent's interests and preferences. To this end, this article proposes DISARM, a novel distributed reputation model. DISARM deals MASs as social networks, enabling agents to establish and maintain relationships, limiting the disadvantages of the common distributed approaches. Additionally, it is based on defeasible logic, modeling the way intelligent agents, like humans, draw reasonable conclusions from incomplete and possibly conflicting (thus inconclusive) information. Finally, we provide an evaluation that illustrates the usability of the proposed model.

Includes members:
  Member "a generic trust framework for large scale open systems using machine learning":
    also connected through other hyperedges:
      (none)
  Member "propositional defeasible logic has linear complexity":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "rethinking defeasible reasoning a scalable approach")
  Member "representation results for defeasible logic":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "rethinking defeasible reasoning a scalable approach")

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)