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 "reasoning about discrete and continuous noisy sensors and effectors in dynamical systems"):
  Abstract: Among the many approaches for reasoning about degrees of belief in the presence of noisy sensing and acting, the logical account proposed by Bacchus, Halpern, and Levesque is perhaps the most expressive. While their formalism is quite general, it is restricted to fluents whose values are drawn from discrete finite domains, as opposed to the continuous domains seen in many robotic applications. In this work, we show how this limitation in that approach can be lifted. By dealing seamlessly with both discrete distributions and continuous densities within a rich theory of action, we provide a very general logical specification of how belief should change after acting and sensing in complex noisy domains.

Includes members:
  Member "robot location estimation in the situation calculus":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "reasoning about probabilities in dynamic systems using goal regression")
  Member "reasoning about probabilities in dynamic systems using goal regression":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "robot location estimation in the situation calculus")
  Member "action networks a framework for reasoning about actions and change under uncertainty":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "robot location estimation in the situation calculus")
  Member "probabilistic reasoning with answer sets":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "semiring programming a declarative framework for generalized sum product problems")
  Member "modelling mixed discrete continuous domains for planning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "timeline based planning expressiveness and complexity")
  Member "decision theoretic planning structural assumptions and computational leverage":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "optimal by design model driven synthesis of adaptation strategies for autonomous systems")
  Member "reasoning about noisy sensors and effectors in the situation calculus":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a first order logic for reasoning about knowledge and probability")

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)