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: "a logic for reasoning about evidence"
  Abstract: We introduce a logic for reasoning about evidence, that essentially views evidence as a function from prior beliefs (before making an observation) to posterior beliefs (after making the observation). We provide a sound and complete axiomatization for the logic, and consider the complexity of the decision problem. Although the reasoning in the logic is mainly propositional, we allow variables representing numbers and quantification over them. This expressive power seems necessary to capture important properties of evidence

Connected through hyperedge HE-1 (induced by source paper "time stamped claim logic"):
  with members:
    - "a formal approach to analyzing cyber forensics evidence"
    - "justifications for common knowledge"

Connected through hyperedge HE-2 (induced by source paper "evidence with uncertain likelihoods"):
  with members:
    - "probabilistic algorithmic knowledge"

Connected through hyperedge HE-3 (induced by source paper "sensitivity analysis in bayesian networks from single to multiple parameters"):
  with members:
    - "sensitivity analysis for probability assessments in bayesian networks"
    - "a differential approach to inference in bayesian networks"
    - "user interface tools for navigation in conditional probability tables and elicitation of probabilities in bayesian networks"
    - "making sensitivity analysis computationally efficient"
    - "when do numbers really matter"

Connected through hyperedge HE-4 (induced by source paper "probabilistic algorithmic knowledge"):
  with members:
    - "modeling adversaries in a logic for security protocol analysis"

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)