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 "exception based knowledge updates"):
  Abstract: Existing methods for dealing with knowledge updates differ greatly depending on the underlying knowledge representation formalism. When Classical Logic is used, updates are typically performed by manipulating the knowledge base on the model-theoretic level. On the opposite side of the spectrum stand the semantics for updating Answer-Set Programs that need to rely on rule syntax. Yet, a unifying perspective that could embrace both these branches of research is of great importance as it enables a deeper understanding of all involved methods and principles and creates room for their cross-fertilisation, ripening and further development. #R##N#This paper bridges the seemingly irreconcilable approaches to updates. It introduces a novel monotonic characterisation of rules, dubbed RE-models, and shows it to be a more suitable semantic foundation for rule updates than SE-models. Then it proposes a generic scheme for specifying semantic rule update operators, based on the idea of viewing a program as the set of sets of RE-models of its rules; updates are performed by introducing additional interpretations - exceptions - to the sets of RE-models of rules in the original program. The introduced scheme is used to define rule update operators that are closely related to both classical update principles and traditional approaches to rules updates, and serve as a basis for a solution to the long-standing problem of state condensing, showing how they can be equivalently defined as binary operators on some class of logic programs. #R##N#Finally, the essence of these ideas is extracted to define an abstract framework for exception-based update operators, viewing a knowledge base as the set of sets of models of its elements, which can capture a wide range of both model- and formula-based classical update operators, and thus serves as the first firm formal ground connecting classical and rule updates.

Includes members:
  Member "the rise and fall of semantic rule updates based on se models":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "syntax preserving belief change operators for logic programs")
  Member "on the evolution of the instance level of dl lite knowledge bases":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on expansion and contraction of dl lite knowledge bases")
  Member "splitting and updating hybrid knowledge bases":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "towards efficient evolving multi context systems preliminary report")
  Member "updates in answer set programming an approach based on basic structural properties":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "syntax preserving belief change operators for logic programs")
  Member "an abductive framework for computing knowledge base updates":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "when you must forget beyond strong persistence when forgetting in answer set programming")
  Member "strong equivalence made easy nested expressions and weight constraints":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on uniform equivalence of epistemic logic programs")
  Member "on properties of update sequences based on causal rejection":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "belief base revision for further improvement of unified answer set programming")

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)