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 "idle time optimization for target assignment and path finding in sortation centers"):
  Abstract: In this paper, we study the one-shot and lifelong versions of the Target Assignment and Path Finding problem in automated sortation centers, where each agent needs to constantly assign itself a sorting station, move to its assigned station without colliding with obstacles or other agents, wait in the queue of that station to obtain a parcel for delivery, and then deliver the parcel to a sorting bin. The throughput of such centers is largely determined by the total idle time of all stations since their queues can frequently become empty. To address this problem, we first formalize and study the one-shot version that assigns stations to a set of agents and finds collision-free paths for the agents to their assigned stations. We present efficient algorithms for this task based on a novel min-cost max-flow formulation that minimizes the total idle time of all stations in a fixed time window. We then demonstrate how our algorithms for solving the one-shot problem can be applied to solving the lifelong problem as well. Experimentally, we believe to be the first researchers to consider real-world automated sortation centers using an industrial simulator with realistic data and a kinodynamic model of real robots. On this simulator, we showcase the benefits of our algorithms by demonstrating their efficiency and effectiveness for up to 350 agents.

Includes members:
  Member "multi agent pathfinding definitions variants and benchmarks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "ddm fast near optimal multi robot path planning using diversified path and optimal sub problem solution database heuristics")
  Member "searching with consistent prioritization for multi agent path finding":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "prioritized multi agent path finding for differential drive robots")
  Member "lifelong path planning with kinematic constraints for multi agent pickup and delivery":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "multi agent pathfinding definitions variants and benchmarks")
  Member "lifelong multi agent path finding for online pickup and delivery tasks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "efficient multi agent motion planning in continuous workspaces using medial axis based swap graphs")
  Member "ai buzzwords explained multi agent path finding mapf":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "multi agent pathfinding definitions variants and benchmarks")
  Member "optimal target assignment and path finding for teams of agents":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a job assignment heuristic for lifelong multi agent path finding problem with multiple delivery locations")
  Member "multi agent path planning and network flow":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "learning safe unlabeled multi robot planning with motion constraints")
  Member "planning optimal paths for multiple robots on graphs":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "drrt scalable and informed asymptotically optimal multi robot 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)