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 "strips action discovery"):
  Abstract: The problem of specifying high-level knowledge bases for planning becomes a hard task in realistic environments. This knowledge is usually handcrafted and is hard to keep updated, even for system experts. Recent approaches have shown the success of classical planning at synthesizing action models even when all intermediate states are missing. These approaches can synthesize action schemas in Planning Domain Definition Language (PDDL) from a set of execution traces each consisting, at least, of an initial and final state. In this paper, we propose a new algorithm to unsupervisedly synthesize STRIPS action models with a classical planner when action signatures are unknown. In addition, we contribute with a compilation to classical planning that mitigates the problem of learning static predicates in the action model preconditions, exploits the capabilities of SAT planners with parallel encodings to compute action schemas and validate all instances. Our system is flexible in that it supports the inclusion of partial input information that may speed up the search. We show through several experiments how learned action models generalize over unseen planning instances.

Includes members:
  Member "learning strips action models with classical planning":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "neural symbolic descriptive action model from images the search for strips")
  Member "learning first order symbolic representations for planning from the structure of the state space":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "causality for machine learning")
  Member "classical planning in deep latent space bridging the subsymbolic symbolic boundary":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "alfred a benchmark for interpreting grounded instructions for everyday tasks")
  Member "learning strips operators from noisy and incomplete observations":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "unsupervised grounding of plannable first order logic representation from images")
  Member "learning partially observable deterministic action models":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "pddlgym gym environments from pddl problems")
  Member "the fast downward planning system":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "transferable task execution from pixels through deep planning domain learning")

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)