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 "stylus a temporal logic optimal control synthesis algorithm for large scale multi robot systems"):
  Abstract: This paper proposes proposes a new highly scalable optimal control synthesis algorithm from linear temporal logic specifications, called $\text{STyLuS}^{*}$ for large-Scale optimal Temporal Logic Synthesis, that is designed to solve complex temporal planning problems in large-scale multi-robot systems. Existing planning approaches with temporal logic specifications rely on graph search techniques applied to a product automaton constructed among the robots. In our previous work, we have proposed a more tractable sampling-based algorithm that builds incrementally trees that approximate the state-space and transitions of the synchronous product automaton and does not require sophisticated graph search techniques. Here, we extend our previous work by introducing 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. This allows us to synthesize optimal motion plans from product automata with hundreds of orders more states than those that existing optimal control synthesis methods or off-the-shelf model checkers can manipulate. We show that $\text{STyLuS}^{*}$ is probabilistically complete and asymptotically optimal and has exponential convergence rate. This is the first time that convergence rate results are provided for sampling-based optimal control synthesis methods. We provide simulation results that show that $\text{STyLuS}^{*}$ can synthesize optimal motion plans for very large multi-robot systems which is impossible using state-of-the-art methods.

Includes members:
  Member "probabilistically safe corridors to guide sampling based motion planning":
    also connected through other hyperedges:
      (none)
  Member "monte carlo tree search for efficient visually guided rearrangement planning":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "goal conditioned end to end visuomotor control for versatile skill primitives")
  Member "t a heuristic search based algorithm for motion planning with temporal goals":
    also connected through other hyperedges:
      (none)
  Member "control of magnetic microrobot teams for temporal micromanipulation tasks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "an abstraction free method for multi robot temporal logic optimal control synthesis")
  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 "an abstraction free method for multi robot temporal logic optimal control synthesis")
  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 "an abstraction free method for multi robot temporal logic optimal control synthesis")

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)