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 "stripstream integrating symbolic planners and blackbox samplers"):
  Abstract: Many planning applications involve complex relationships defined on high-dimensional, continuous variables. For example, robotic manipulation requires planning with kinematic, collision, and motion constraints involving robot configurations, object transforms, and robot trajectories. These constraints typically require specialized procedures to sample satisfying values. We extend the STRIPS planning language to support a generic, declarative specification for these procedures while treating their implementation as blackboxes. We provide several domain-independent algorithms that reduce STRIPStream problems to a sequence of finite-domain STRIPS planning problems. Additionally, we describe cost-sensitive planning within this framework. Finally, we evaluate our algorithms on three robotic task and motion planning domains.

Includes members:
  Member "sampling based methods for factored task and motion planning":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "reactive navigation in partially familiar planar environments using semantic perceptual feedback")
  Member "modelling mixed discrete continuous domains for planning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "timeline based planning expressiveness and complexity")
  Member "the fast downward planning system":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "transferable task execution from pixels through deep planning domain learning")
  Member "pddl2 1 an extension to pddl for expressing temporal planning domains":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "transferable task execution from pixels through deep planning domain learning")
  Member "the metric ff planning system translating ignoring delete lists to numeric state variables":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "what should i do now marrying reinforcement learning and symbolic planning")
  Member "the 3rd international planning competition results and analysis":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "learning domain independent planning heuristics with hypergraph networks")

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)