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: "reasoning about soft constraints and conditional preferences complexity results and approximation techniques"
  Abstract: Many real life optimization problems contain both hard and soft constraints, as well as qualitative conditional preferences. However, there is no single formalism to specify all three kinds of information. We therefore propose a framework, based on both CP-nets and soft constraints, that handles both hard and soft constraints as well as conditional preferences efficiently and uniformly. We study the complexity of testing the consistency of preference statements, and show how soft constraints can faithfully approximate the semantics of conditional preference statements whilst improving the computational complexity

Connected through hyperedge HE-1 (induced by source paper "rank pruning for dominance queries in cp nets"):
  with members:
    - "ucp networks a directed graphical representation of conditional utilities"
    - "the computational complexity of dominance and consistency in cp nets"
    - "cp nets a tool for representing and reasoning with conditional ceteris paribus preference statements"

Connected through hyperedge HE-2 (induced by source paper "logical conditional preference theories"):
  with members:
    - "xsb extending prolog with tabled logic programming"
    - "the computational complexity of dominance and consistency in cp nets"
    - "cp nets a tool for representing and reasoning with conditional ceteris paribus preference statements"

Connected through hyperedge HE-3 (induced by source paper "compact value function representations for qualitative preferences"):
  with members:
    - "graphical models for preference and utility"
    - "ucp networks a directed graphical representation of conditional utilities"
    - "introducing variable importance tradeoffs into cp nets"
    - "cp nets a tool for representing and reasoning with conditional ceteris paribus preference statements"

Connected through hyperedge HE-4 (induced by source paper "more or less cp networks"):
  with members:
    - "graphical models for preference and utility"
    - "ucp networks a directed graphical representation of conditional utilities"
    - "cp nets a tool for representing and reasoning with conditional ceteris paribus preference statements"

Connected through hyperedge HE-5 (induced by source paper "the computational complexity of dominance and consistency in cp nets"):
  with members:
    - "introducing variable importance tradeoffs into cp nets"
    - "on graphical modeling of preference and importance"
    - "cp nets a tool for representing and reasoning with conditional ceteris paribus preference statements"
    - "structure and complexity in planning with unary operators"

Connected through hyperedge HE-6 (induced by source paper "on graphical modeling of preference and importance"):
  with members:
    - "ucp networks a directed graphical representation of conditional utilities"
    - "possibilistic constraint satisfaction problems or how to handle soft constraints"
    - "compact value function representations for qualitative preferences"
    - "the computational complexity of dominance and consistency in cp nets"
    - "cp nets a tool for representing and reasoning with conditional ceteris paribus preference statements"
    - "logic programming with ordered disjunction"

Connected through hyperedge HE-7 (induced by source paper "cp nets a tool for representing and reasoning with conditional ceteris paribus preference statements"):
  with members:
    - "graphical models for preference and utility"
    - "utility elicitation as a classification problem"
    - "expected utility networks"
    - "ucp networks a directed graphical representation of conditional utilities"
    - "conditional utility utility independence and utility networks"
    - "structure and complexity in planning with unary operators"

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)