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 "path finding for the coalition of co operative agents acting in the environment with destructible obstacles"):
  Abstract: The problem of planning a set of paths for the coalition of robots (agents) with different capabilities is considered in the paper. Some agents can modify the environment by destructing the obstacles thus allowing the other ones to shorten their paths to the goal. As a result the mutual solution of lower cost, e.g. time to completion, may be acquired. We suggest an original procedure to identify the obstacles for further removal that can be embedded into almost any heuristic search planner (we use Theta*) and evaluate it empirically. Results of the evaluation show that time-to-complete the mission can be decreased up to 9-12 % by utilizing the proposed technique.

Includes members:
  Member "behavior and path planning for the coalition of cognitive robots in smart relocation tasks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "psychologically inspired planning method for smart relocation task")
  Member "applying mapp algorithm for cooperative path finding in urban environments":
    also connected through other hyperedges:
      (none)
  Member "any angle pathfinding for multiple agents based on sipp algorithm":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multi agent pathfinding definitions variants and benchmarks")
  Member "psychologically inspired planning method for smart relocation task":
    also connected through other hyperedges:
      (none)
  Member "mapp a scalable multi agent path planning algorithm with tractability and completeness guarantees":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "ddm fast near optimal multi robot path planning using diversified path and optimal sub problem solution database heuristics")
  Member "theta any angle path planning on grids":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "perception driven sparse graphs for optimal motion planning")

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)