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: "defeasible logic programming an argumentative approach"
  Abstract: The work reported here introduces Defeasible Logic Programming (DeLP), a formalism that combines results of Logic Programming and Defeasible Argumentation. DeLP provides the possibility of representing information in the form of weak rules in a declarative manner, and a defeasible argumentation inference mechanism for warranting the entailed conclusions. #R##N#In DeLP an argumentation formalism will be used for deciding between contradictory goals. Queries will be supported by arguments that could be defeated by other arguments. A query q will succeed when there is an argument A for q that is warranted, ie, the argument A that supports q is found undefeated by a warrant procedure that implements a dialectical analysis. #R##N#The defeasible argumentation basis of DeLP allows to build applications that deal with incomplete and contradictory information in dynamic domains. Thus, the resulting approach is suitable for representing agent's knowledge and for providing an argumentation based reasoning mechanism to agents.

Connected through hyperedge HE-1 (induced by source paper "cognitive argumentation and the suppression task"):
  with members:
    - "a general account of argumentation with preferences"

Connected through hyperedge HE-2 (induced by source paper "neural symbolic argumentation mining an argument in favour of deep learning and reasoning"):
  with members:
    - "deep learning for sentiment analysis a survey"
    - "argument component classification for classroom discussions"
    - "multi task learning for argumentation mining in low resource settings"
    - "what is the essence of a claim cross domain claim identification"
    - "deep residual learning for weakly supervised relation extraction"
    - "argument mining with structured svms and rnns"
    - "logic tensor networks deep learning and logical reasoning from data and knowledge"

Connected through hyperedge HE-3 (induced by source paper "a comparative study of some central notions of aspic and delp"):
  with members:
    - "a general account of argumentation with preferences"

Connected through hyperedge HE-4 (induced by source paper "representation justification and explanation in a value driven agent an argumentation based approach"):
  with members:
    - "building jiminy cricket an architecture for moral agreements among stakeholders"
    - "a symbolic approach to explaining bayesian network classifiers"
    - "towards a grounded dialog model for explainable artificial intelligence"
    - "explanation in artificial intelligence insights from the social sciences"
    - "prioritized norms in formal argumentation"

Connected through hyperedge HE-5 (induced by source paper "principles and examples of plausible reasoning and propositional plausible logic"):
  with members:
    - "a general account of argumentation with preferences"
    - "what does a conditional knowledge base entail"
    - "nonmonotonic reasoning preferential models and cumulative logics"

Connected through hyperedge HE-6 (induced by source paper "on the links between argumentation based reasoning and nonmonotonic reasoning"):
  with members:
    - "a general account of argumentation with preferences"
    - "nonmonotonic reasoning preferential models and cumulative logics"

Connected through hyperedge HE-7 (induced by source paper "an approach to decision making based on dynamic argumentation systems"):
  with members:
    - "introducing variable importance tradeoffs into cp nets"

Connected through hyperedge HE-8 (induced by source paper "two forms of minimality in aspic"):
  with members:
    - "a general account of argumentation with preferences"

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)