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: "ucp networks a directed graphical representation of conditional utilities"
  Abstract: We propose a new directed graphical representation of utility functions, called UCP-networks, that combines aspects of two existing graphical models: generalized additive models and CP-networks. The network decomposes a utility function into a number of additive factors, with the directionality of the arcs reflecting conditional dependence of preference statements - in the underlying (qualitative) preference ordering - under a {em ceteris paribus} (all else being equal) interpretation. This representation is arguably natural in many settings. Furthermore, the strong CP-semantics ensures that computation of optimization and dominance queries is very efficient. We also demonstrate the value of this representation in decision making. Finally, we describe an interactive elicitation procedure that takes advantage of the linear nature of the constraints on "`tradeoff weights" imposed by a UCP-network. This procedure allows the network to be refined until the regret of the decision with minimax regret (with respect to the incompletely specified utility function) falls below a specified threshold (e.g., the cost of further questioning.

Connected through hyperedge HE-1 (induced by source paper "gradient based optimization for bayesian preference elicitation"):
  with members:
    - "a cost effective framework for preference elicitation and aggregation"
    - "constructive preference elicitation over hybrid combinatorial spaces"
    - "adam a method for stochastic optimization"
    - "local utility elicitation in gai models"

Connected through hyperedge HE-2 (induced by source paper "rank pruning for dominance queries in cp nets"):
  with members:
    - "reasoning about soft constraints and conditional preferences complexity results and approximation techniques"
    - "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 "on the decomposition of generalized additive independence models"):
  with members:
    - "graphical models for preference and utility"

Connected through hyperedge HE-4 (induced by source paper "probabilistic conditional preference networks"):
  with members:
    - "cp nets a tool for representing and reasoning with conditional ceteris paribus preference statements"

Connected through hyperedge HE-5 (induced by source paper "unstructuring user preferences efficient non parametric utility revelation"):
  with members:
    - "graphical models for preference and utility"
    - "expected utility networks"
    - "a hybrid approach to reasoning with partially elicited preference models"
    - "compact value function representations for qualitative preferences"
    - "cp nets a tool for representing and reasoning with conditional ceteris paribus preference statements"

Connected through hyperedge HE-6 (induced by source paper "compact value function representations for qualitative preferences"):
  with members:
    - "graphical models for preference and utility"
    - "introducing variable importance tradeoffs into cp nets"
    - "reasoning about soft constraints and conditional preferences complexity results and approximation techniques"
    - "cp nets a tool for representing and reasoning with conditional ceteris paribus preference statements"

Connected through hyperedge HE-7 (induced by source paper "regret minimizing equilibria and mechanisms for games with strict type uncertainty"):
  with members:
    - "complexity of mechanism design"
    - "cooperative negotiation in autonomic systems using incremental utility elicitation"
    - "bundling equilibrium in combinatorial auctions"

Connected through hyperedge HE-8 (induced by source paper "more or less cp networks"):
  with members:
    - "graphical models for preference and utility"
    - "reasoning about soft constraints and conditional preferences complexity results and approximation techniques"
    - "cp nets a tool for representing and reasoning with conditional ceteris paribus preference statements"

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)