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 "an abstraction free method for multi robot temporal logic optimal control synthesis"):
  Abstract: The majority of existing Linear Temporal Logic (LTL) planning methods rely on the construction of a discrete product automaton, that combines a discrete abstraction of robot mobility and a B$\ddot{\text{u}}$chi automaton that captures the LTL specification. Representing this product automaton as a graph and using graph search techniques, optimal plans that satisfy the LTL task can be synthesized. However, constructing expressive discrete abstractions makes the synthesis problem computationally intractable. In this paper, we propose a new sampling-based LTL planning algorithm that does not require any discrete abstraction of robot mobility. Instead, it builds incrementally trees that explore the product state-space, until a maximum number of iterations is reached or a feasible plan is found. The use of trees makes data storing and manipulation tractable, which significantly increases the scalability of our algorithm. To accelerate the construction of feasible plans, we introduce bias in the sampling process which is guided by transitions in the B$\ddot{\text{u}}$chi automaton that belong to the shortest path to the accepting states. We show that our planning algorithm is probabilistically complete and asymptotically optimal. Finally, we present numerical experiments showing that our method outperforms relevant temporal logic planning methods.

Includes members:
  Member "stylus a temporal logic optimal control synthesis algorithm for large scale multi robot systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hyperproperties for robotics planning via hyperltl")
  Member "control of magnetic microrobot teams for temporal micromanipulation tasks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "stylus a temporal logic optimal control synthesis algorithm for large scale multi robot systems")
  Member "learning sampling distributions for robot motion planning":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "accelerating cooperative planning for automated vehicles with learned heuristics and monte carlo tree search")
  Member "decentralized abstractions for multi agent systems under coupled constraints":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "stylus a temporal logic optimal control synthesis algorithm for large scale multi robot systems")
  Member "sampling based temporal logic path planning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "control synthesis from linear temporal logic specifications using model free reinforcement learning")
  Member "optimal multi robot path planning with ltl constraints guaranteeing correctness through synchronization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "stylus a temporal logic optimal control synthesis algorithm for large scale multi robot systems")
  Member "sampling based algorithms for optimal motion planning":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "3d dynamic scene graphs actionable spatial perception with places objects and humans")
  Member "synthesis of distributed control and communication schemes from global ltl specifications":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "stylus a temporal logic optimal control synthesis algorithm for large scale multi robot systems")

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.RO(Robotics)