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: "on automating the doctrine of double effect"
  Abstract: The doctrine of double effect ($\mathcal{DDE}$) is a long-studied ethical principle that governs when actions that have both positive and negative effects are to be allowed. The goal in this paper is to automate $\mathcal{DDE}$. We briefly present $\mathcal{DDE}$, and use a first-order modal logic, the deontic cognitive event calculus, as our framework to formalize the doctrine. We present formalizations of increasingly stronger versions of the principle, including what is known as the doctrine of triple effect. We then use our framework to simulate successfully scenarios that have been used to test for the presence of the principle in human subjects. Our framework can be used in two different modes: One can use it to build $\mathcal{DDE}$-compliant autonomous systems from scratch, or one can use it to verify that a given AI system is $\mathcal{DDE}$-compliant, by applying a $\mathcal{DDE}$ layer on an existing system or model. For the latter mode, the underlying AI system can be built using any architecture (planners, deep neural networks, bayesian networks, knowledge-representation systems, or a hybrid); as long as the system exposes a few parameters in its model, such verification is possible. The role of the $\mathcal{DDE}$ layer here is akin to a (dynamic or static) software verifier that examines existing software modules. Finally, we end by presenting initial work on how one can apply our $\mathcal{DDE}$ layer to the STRIPS-style planning model, and to a modified POMDP model.This is preliminary work to illustrate the feasibility of the second mode, and we hope that our initial sketches can be useful for other researchers in incorporating DDE in their own frameworks.

Connected through hyperedge HE-1 (induced by source paper "designing normative theories of ethical reasoning formal framework methodology and tool support"):
  with members:
    - "a computational hermeneutic approach for conceptual explicitation"
    - "grunge a grand unified atp challenge"
    - "computer science and metaphysics a cross fertilization"
    - "harnessing higher order meta logic to represent and reason with complex ethical theories"
    - "extensional higher order paramodulation in leo iii"
    - "building jiminy cricket an architecture for moral agreements among stakeholders"
    - "i o logic in hol first steps"
    - "the higher order prover leo iii"

Connected through hyperedge HE-2 (induced by source paper "harnessing higher order meta logic to represent and reason with complex ethical theories"):
  with members:
    - "designing normative theories of ethical reasoning formal framework methodology and tool support"
    - "deontic logic for human reasoning"

Connected through hyperedge HE-3 (induced by source paper "learning textit ex nihilo"):
  with members:
    - "automating godel s ontological proof of god s existence with higher order automated theorem provers"

Connected through hyperedge HE-4 (induced by source paper "impossibility and uncertainty theorems in ai value alignment or why your agi should not have a utility function"):
  with members:
    - "trial without error towards safe reinforcement learning via human intervention"
    - "the social dilemma of autonomous vehicles"
    - "cooperative inverse reinforcement learning"
    - "inherent trade offs in the fair determination of risk scores"
    - "a definition of happiness for reinforcement learning agents"

Connected through hyperedge HE-5 (induced by source paper "toward cognitive and immersive systems experiments in a cognitive microworld"):
  with members:
    - "clevr a diagnostic dataset for compositional language and elementary visual reasoning"

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)