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 "a multi engine approach to answer set programming"):
  Abstract: Answer-set programming (ASP) is a truly declarative programming paradigm proposed in the area of non-monotonic reasoning and logic programming, which has been recently employed in many applications. The development of efficient ASP systems is, thus, crucial. Having in mind the task of improving the solving methods for ASP, there are two usual ways to reach this goal: (i) extending state-of-the-art techniques and ASP solvers or (ii) designing a new ASP solver from scratch. An alternative to these trends is to build on top of state-of-the-art solvers, and to apply machine learning techniques for choosing automatically the “best” available solver on a per-instance basis.  In this paper, we pursue this latter direction. We first define a set of cheap-to-compute syntactic features that characterize several aspects of ASP programs. Then, we apply classification methods that, given the features of the instances in a  training  set and the solvers' performance on these instances, inductively learn algorithm selection strategies to be applied to a  test  set. We report the results of a number of experiments considering solvers and different training and test sets of instances taken from the ones submitted to the “System Track” of the Third ASP Competition. Our analysis shows that by applying machine learning techniques to ASP solving, it is possible to obtain very robust performance: our approach can solve more instances compared with any solver that entered the Third ASP Competition.

Includes members:
  Member "the third open answer set programming competition":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the seventh answer set programming competition design and results")
  Member "team building with answer set programming in the gioia tauro seaport":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "efficiently coupling the i dlv grounder with asp solvers")
  Member "detecting inconsistencies in large biological networks with answer set programming":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a logic based framework leveraging neural networks for studying the evolution of neurological disorders")
  Member "satzilla portfolio based algorithm selection for sat":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "deciding the consistency of non linear real arithmetic constraints with a conflict driven search using cylindrical algebraic coverings")
  Member "the dlv system for knowledge representation and reasoning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the seventh answer set programming competition design and results")
  Member "stable models and an alternative logic programming paradigm":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "the seventh answer set programming competition design and results")

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)