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: "probabilistic evaluation of sequential plans from causal models with hidden variables"
  Abstract: The paper concerns the probabilistic evaluation of plans in the presence of unmeasured variables, each plan consisting of several concurrent or sequential actions. We establish a graphical criterion for recognizing when the effects of a given plan can be predicted from passive observations on measured variables only. When the criterion is satisfied, a closed-form expression is provided for the probability that the plan will achieve a specified goal.

Connected through hyperedge HE-1 (induced by source paper "efficiently learning and sampling interventional distributions from observations"):
  with members:
    - "efficient distance approximation for structured high dimensional distributions via learning"
    - "learning and testing causal models with interventions"
    - "identifiability and transportability in dynamic causal networks"
    - "testing bayesian networks"
    - "estimating the causal impact of recommendation systems from observational data"
    - "axiomatizing causal reasoning"
    - "testing identifiability of causal effects"
    - "causal networks semantics and expressiveness"

Connected through hyperedge HE-2 (induced by source paper "a general algorithm for deciding transportability of experimental results"):
  with members:
    - "axiomatizing causal reasoning"
    - "testing identifiability of causal effects"
    - "direct and indirect effects"
    - "identification of conditional interventional distributions"
    - "causal inference by surrogate experiments z identifiability"
    - "pearl s calculus of intervention is complete"

Connected through hyperedge HE-3 (induced by source paper "testing identifiability of causal effects"):
  with members:
    - "a probabilistic calculus of actions"

Connected through hyperedge HE-4 (induced by source paper "identification of conditional interventional distributions"):
  with members:
    - "axiomatizing causal reasoning"
    - "direct and indirect effects"
    - "identifying conditional causal effects"

Connected through hyperedge HE-5 (induced by source paper "identifying optimal sequential decisions"):
  with members:
    - "causal networks semantics and expressiveness"
    - "identification of conditional interventional distributions"
    - "identifying conditional causal effects"

Connected through hyperedge HE-6 (induced by source paper "causal inference by surrogate experiments z identifiability"):
  with members:
    - "axiomatizing causal reasoning"
    - "testing identifiability of causal effects"

Connected through hyperedge HE-7 (induced by source paper "pearl s calculus of intervention is complete"):
  with members:
    - "testing identifiability of causal effects"
    - "on the testable implications of causal models with hidden variables"

Connected through hyperedge HE-8 (induced by source paper "identifying dynamic sequential plans"):
  with members:
    - "identifying conditional causal effects"
    - "decision theoretic foundations for causal 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)