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: "actual causation in cp logic"
  Abstract: Given a causal model of some domain and a particular story that has taken place in this domain, the problem of actual causation is deciding which of the possible causes for some effect actually caused it. One of the most influential approaches to this problem has been developed by Halpern and Pearl in the context of structural models. In this paper, I argue that this is actually not the best setting for studying this problem. As an alternative, I offer the probabilistic logic programming language of CP-logic. Unlike structural models, CP-logic incorporates the deviant/default distinction that is generally considered an important aspect of actual causation, and it has an explicitly dynamic semantics, which helps to formalize the stories that serve as input to an actual causation problem.

Connected through hyperedge HE-1 (induced by source paper "enablers and inhibitors in causal justifications of logic programs"):
  with members:
    - "justifying answer sets using argumentation"
    - "causal graph justifications of logic programs"
    - "catching the ouroboros on debugging non ground answer set programs"
    - "actual causation and the art of modeling"
    - "defaults and normality in causal structures"
    - "justifications for logic programs under answer set semantics"
    - "stable models and an alternative logic programming paradigm"

Connected through hyperedge HE-2 (induced by source paper "justifications for programs with disjunctive and causal choice rules"):
  with members:
    - "enablers and inhibitors in causal justifications of logic programs"
    - "deriving conclusions from non monotonic cause effect relations"
    - "justifying answer sets using argumentation"
    - "causal graph justifications of logic programs"
    - "catching the ouroboros on debugging non ground answer set programs"
    - "justifications for logic programs under answer set semantics"
    - "stable models and an alternative logic programming paradigm"

Connected through hyperedge HE-3 (induced by source paper "deriving conclusions from non monotonic cause effect relations"):
  with members:
    - "enablers and inhibitors in causal justifications of logic programs"
    - "justifications for programs with disjunctive and causal choice rules"
    - "justifying answer sets using argumentation"
    - "causal graph justifications of logic programs"
    - "defaults and normality in causal structures"
    - "justifications for logic programs under answer set semantics"

Connected through hyperedge HE-4 (induced by source paper "combining probabilistic causal and normative reasoning in cp logic"):
  with members:
    - "towards a general framework for actual causation using cp logic"
    - "probabilistic definitions of actual causation using cp logic"
    - "graded causation and defaults"
    - "cp logic a language of causal probabilistic events and its relation to logic programming"

Connected through hyperedge HE-5 (induced by source paper "causal graph justifications of logic programs"):
  with members:
    - "an algebra of causal chains"
    - "defaults and normality in causal structures"
    - "justifications for logic programs under answer set semantics"

Connected through hyperedge HE-6 (induced by source paper "towards a general framework for actual causation using cp logic"):
  with members:
    - "graded causation and defaults"
    - "causes and explanations a structural model approach part ii explanations"

Connected through hyperedge HE-7 (induced by source paper "probabilistic definitions of actual causation using cp logic"):
  with members:
    - "graded causation and defaults"
    - "causes and explanations a structural model approach part ii explanations"

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)