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 "strategy synthesis in pomdps via game based abstractions"):
  Abstract: We study synthesis problems with constraints in partially observable Markov decision processes (POMDPs), where the objective is to compute a strategy for an agent that is guaranteed to satisfy certain safety and performance specifications. Verification and strategy synthesis for POMDPs are, however, computationally intractable in general. We alleviate this difficulty by focusing on planning applications and exploiting typical structural properties of such scenarios; for instance, we assume that the agent has the ability to observe its own position inside an environment. We propose an abstraction refinement framework which turns such a POMDP model into a (fully observable) probabilistic two-player game (PG). For the obtained PGs, efficient verification and synthesis tools allow to determine strategies with optimal safety and performance measures, which approximate optimal schedulers on the POMDP. If the approximation is too coarse to satisfy the given specifications, an refinement scheme improves the computed strategies. As a running example, we use planning problems where an agent moves inside an environment with randomly moving obstacles and restricted observability. We demonstrate that the proposed method advances the state of the art by solving problems several orders-of-magnitude larger than those that can be handled by existing POMDP solvers. Furthermore, this method gives guarantees on safety constraints, which is not supported by the majority of the existing solvers.

Includes members:
  Member "human in the loop synthesis for partially observable markov decision processes":
    also connected through other hyperedges:
      (none)
  Member "counterexample guided abstraction refinement for pomdps":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "supervisor synthesis of pomdp based on automata learning")
  Member "a storm is coming a modern probabilistic model checker":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the probabilistic model checker storm")
  Member "motion planning under partial observability using game based abstraction":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "human in the loop synthesis for partially observable markov decision processes")
  Member "reinforcement learning of pomdps using spectral methods":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "regret bound of adaptive control in linear quadratic gaussian lqg systems")
  Member "optimal cost almost sure reachability in pomdps":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "counterexample driven synthesis for probabilistic program sketches")
  Member "qualitative analysis of pomdps with temporal logic specifications for robotics applications":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "point based methods for model checking in partially observable markov decision processes")
  Member "discretized approximations for pomdp with average cost":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "reinforcement learning for pomdp partitioned rollout and policy iteration with application to autonomous sequential repair problems")

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)