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 "on the qualitative comparison of decisions having positive and negative features"):
  Abstract: Making a decision is often a matter of listing and comparing positive and negative arguments. In such cases, the evaluation scale for decisions should be considered bipolar, that is, negative and positive values should be explicitly distinguished. That is what is done, for example, in Cumulative Prospect Theory. However, contrary to the latter framework that presupposes genuine numerical assessments, human agents often decide on the basis of an ordinal ranking of the pros and the cons, and by focusing on the most salient arguments. In other terms, the decision process is qualitative as well as bipolar. In this article, based on a bipolar extension of possibility theory, we define and axiomatically characterize several decision rules tailored for the joint handling of positive and negative arguments in an ordinal setting. The simplest rules can be viewed as extensions of the maximin and maximax criteria to the bipolar case, and consequently suffer from poor decisive power. More decisive rules that refine the former are also proposed. These refinements agree both with principles of efficiency and with the spirit of order-of-magnitude reasoning, that prevails in qualitative decision theory. The most refined decision rule uses leximin rankings of the pros and the cons, and the ideas of counting arguments of equal strength and cancelling pros by cons. It is shown to come down to a special case of Cumulative Prospect Theory, and to subsume the "Take the Best" heuristic studied by cognitive psychologists.

Includes members:
  Member "defining relative likelihood in partially ordered preferential structures":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "weighted regret based likelihood a new approach to describing uncertainty")
  Member "generalized qualitative probability savage revisited":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "belief functions and default reasoning")
  Member "a unified framework for order of magnitude confidence relations":
    also connected through other hyperedges:
      (none)
  Member "using arguments for making decisions a possibilistic logic approach":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a unified setting for inference and decision an argumentation based approach")
  Member "bi capacities part ii the choquet integral":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "bipolarization of posets and natural interpolation")
  Member "graduality in argumentation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "broadening label based argumentation semantics with may must scales")
  Member "cp nets a tool for representing and reasoning with conditional ceteris paribus preference statements":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on validating repairing and refining heuristic ml explanations")

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)