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 "learning features and abstract actions for computing generalized plans"):
  Abstract: Generalized planning is concerned with the computation of plans that solve not one but multiple instances of a planning domain. Recently, it has been shown that generalized plans can be expressed as mappings of feature values into actions, and that they can often be computed with fully observable non-deterministic (FOND) planners. The actions in such plans, however, are not the actions in the instances themselves, which are not necessarily common to other instances, but abstract actions that are defined on a set of common features. The formulation assumes that the features and the abstract actions are given. In this work, we address this limitation by showing how to learn them automatically. The resulting account of generalized planning combines learning and planning in a novel way: a learner, based on a Max SAT formulation, yields the features and abstract actions from sampled state transitions, and a FOND planner uses this information, suitably transformed, to produce the general plans. Correctness guarantees are given and experimental results on several domains are reported.

Includes members:
  Member "composable planning with attributes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "plannable approximations to mdp homomorphisms equivariance under actions")
  Member "features projections and representation change for generalized planning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "qualitative numeric planning reductions and complexity")
  Member "representation learning on graphs methods and applications":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "learning to segment 3d point clouds in 2d image space")
  Member "towards deep symbolic reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "analyzing differentiable fuzzy logic operators")
  Member "mazebase a sandbox for learning from games":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "why build an assistant in minecraft")
  Member "first order decision diagrams for relational mdps":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "qualitative numeric planning reductions and complexity")
  Member "approximate policy iteration with a policy language bias solving relational markov decision processes":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "generalized neural policies for relational mdps")

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)