human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "liability ethics and culture aware behavior specification using rulebooks"
  Abstract: The behavior of self-driving cars must be compatible with an enormous set of conflicting and ambiguous objectives, from law, from ethics, from the local culture, and so on. This paper describes a new way to conveniently define the desired behavior for autonomous agents, which we use on the self-driving cars developed at nuTonomy. We define a "rulebook" as a pre-ordered set of "rules", each akin to a violation metric on the possible outcomes ("realizations"). The rules are partially ordered by priority. The semantics of a rulebook imposes a pre-order on the set of realizations. We study the compositional properties of the rulebooks, and we derive which operations we can allow on the rulebooks to preserve previously-introduced constraints. While we demonstrate the application of these techniques in the self-driving domain, the methods are domain-independent.

Connected through hyperedge HE-1 (induced by source paper "overview of tools supporting planning for automated driving"):
  with members:
    - "self driving cars a survey"
    - "interaction dataset an international adversarial and cooperative motion dataset in interactive driving scenarios with semantic maps"
    - "the apolloscape open dataset for autonomous driving and its application"
    - "design space of behaviour planning for autonomous driving"
    - "a survey of autonomous driving common practices and emerging technologies"
    - "fiesta fast incremental euclidean distance fields for online motion planning of aerial robots"
    - "top view trajectories a pedestrian dataset of vehicle crowd interaction from controlled experiments and crowded campus"
    - "control of connected and automated vehicles state of the art and future challenges"

Connected through hyperedge HE-2 (induced by source paper "automatic testing and falsification with dynamically constrained reinforcement learning"):
  with members:
    - "safe reinforcement learning with scene decomposition for navigating complex urban environments"
    - "falsification of cyber physical systems using deep reinforcement learning"
    - "carla an open urban driving simulator"
    - "a temporal logic approach to modular design of synthetic biological circuits"
    - "playing atari with deep reinforcement learning"

Connected through hyperedge HE-3 (induced by source paper "on maximizing lateral clearance of an autonomous vehicle in urban environments"):
  with members:
    - "pampc perception aware model predictive control for quadrotors"
    - "incremental sampling based algorithm for minimum violation motion planning"
    - "sampling based algorithms for optimal motion planning"

Question: Please tell me which class the center node 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)