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: "argument ranking with categoriser function"
  Abstract: Recently, ranking-based semantics is proposed to rank-order arguments from the most acceptable to the weakest one(s), which provides a graded assessment to arguments. In general, the ranking on arguments is derived from the strength values of the arguments. Categoriser function is a common approach that assigns a strength value to a tree of arguments. When it encounters an argument system with cycles, then the categoriser strength is the solution of the non-linear equations. However, there is no detail about the existence and uniqueness of the solution, and how to find the solution (if exists). In this paper, we will cope with these issues via fixed point technique. In addition, we define the categoriser-based ranking semantics in light of categoriser strength, and investigate some general properties of it. Finally, the semantics is shown to satisfy some of the axioms that a ranking-based semantics should satisfy.

Connected through hyperedge HE-1 (induced by source paper "epistemic graphs for representing and reasoning with positive and negative influences of arguments"):
  with members:
    - "empirical evaluation of abstract argumentation supporting the need for bipolar and probabilistic approaches"
    - "a comparative study of ranking based semantics for abstract argumentation"
    - "winning arguments interaction dynamics and persuasion strategies in good faith online discussions"
    - "afra argumentation framework with recursive attacks"
    - "graduality in argumentation"
    - "probabilistic default reasoning with conditional constraints"

Connected through hyperedge HE-2 (induced by source paper "a comparative study of ranking based semantics for abstract argumentation"):
  with members:
    - "graduality in argumentation"

Connected through hyperedge HE-3 (induced by source paper "some supplementaries to the counting semantics for abstract argumentation"):
  with members:
    - "attacker and defender counting approach for abstract argumentation"
    - "on the acceptability of arguments in preference based argumentation"
    - "graduality in argumentation"

Connected through hyperedge HE-4 (induced by source paper "attacker and defender counting approach for abstract argumentation"):
  with members:
    - "graduality in argumentation"

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)