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: "possibilistic constraint satisfaction problems or how to handle soft constraints"
  Abstract: Many AI synthesis problems such as planning or scheduling may be modelized as constraint satisfaction problems (CSP). A CSP is typically defined as the problem of finding any consistent labeling for a fixed set of variables satisfying all given constraints between these variables. However, for many real tasks such as job-shop scheduling, time-table scheduling, design?, all these constraints have not the same significance and have not to be necessarily satisfied. A first distinction can be made between hard constraints, which every solution should satisfy and soft constraints, whose satisfaction has not to be certain. In this paper, we formalize the notion of possibilistic constraint satisfaction problems that allows the modeling of uncertainly satisfied constraints. We use a possibility distribution over labelings to represent respective possibilities of each labeling. Necessity-valued constraints allow a simple expression of the respective certainty degrees of each constraint. The main advantage of our approach is its integration in the CSP technical framework. Most classical techniques, such as Backtracking (BT), arcconsistency enforcing (AC) or Forward Checking have been extended to handle possibilistics CSP and are effectively implemented. The utility of our approach is demonstrated on a simple design problem.

Connected through hyperedge HE-1 (induced by source paper "human in the loop learning of qualitative preference models"):
  with members:
    - "penalty logic and its link with dempster shafer theory"
    - "cp nets a tool for representing and reasoning with conditional ceteris paribus preference statements"

Connected through hyperedge HE-2 (induced by source paper "tree projections and constraint optimization problems fixed parameter tractability and parallel algorithms"):
  with members:
    - "constraint solving via fractional edge covers"
    - "greedy strategies and larger islands of tractability for conjunctive queries and constraint satisfaction problems"
    - "general and fractional hypertree decompositions hard and easy cases"
    - "aggregations over generalized hypertree decompositions"
    - "faq questions asked frequently"
    - "structural tractability of enumerating csp solutions"
    - "a quasi polynomial time partition oracle for graphs with an excluded minor"
    - "tree projections and structural decomposition methods minimality and game theoretic characterization"

Connected through hyperedge HE-3 (induced by source paper "reasoning about soft constraints and conditional preferences complexity results and approximation techniques"):
  with members:
    - "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-4 (induced by source paper "on graphical modeling of preference and importance"):
  with members:
    - "ucp networks a directed graphical representation of conditional utilities"
    - "compact value function representations for qualitative preferences"
    - "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"
    - "logic programming with ordered disjunction"

Connected through hyperedge HE-5 (induced by source paper "soft constraint programming to analysing security protocols"):
  with members:
    - "soft concurrent constraint programming"

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)