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 "deep tractable probabilistic models for moral responsibility"):
  Abstract: Moral responsibility is a major concern in automated decision-making, with applications ranging from self-driving cars to kidney exchanges. From the viewpoint of automated systems, the urgent questions are: (a) How can models of moral scenarios and blameworthiness be extracted and learnt automatically from data? (b) How can judgements be computed tractably, given the split-second decision points faced by the system? By building on deep tractable probabilistic learning, we propose a learning regime for inducing models of such scenarios automatically from data and reasoning tractably from them. We report on experiments that compare our system with human judgement in three illustrative domains: lung cancer staging, teamwork management, and trolley problems.

Includes members:
  Member "learning and testing causal models with interventions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "efficient distance approximation for structured high dimensional distributions via learning")
  Member "towards formal definitions of blameworthiness intention and moral responsibility":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "efficiently checking actual causality with sat solving")
  Member "a computational model of commonsense moral decision making":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "scaling up psychology via scientific regret minimization a case study in moral decision making")
  Member "a voting based system for ethical decision making":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "mathematical notions vs human perception of fairness a descriptive approach to fairness for machine learning")
  Member "on the latent variable interpretation in sum product networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "advances in machine learning for the behavioral sciences")
  Member "sum product networks a new deep architecture":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "training deep energy based models with f divergence minimization")
  Member "evaluating influence diagrams with decision circuits":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "sensitivity analysis in decision circuits")
  Member "solving sat and bayesian inference with backtracking search":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "semiring programming a declarative framework for generalized sum product 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.AI(Artificial Intelligence)