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: "a probabilistic extension of action language bc"
  Abstract: We present a probabilistic extension of action language BC+. Just like BC+ is defined as a high-level notation of answer set programs for describing transition systems, the proposed language, which we call pBC+, is defined as a high-level notation of LPMLN programs---a probabilistic extension of answer set programs. We show how probabilistic reasoning about transition systems, such as prediction, postdiction, and planning problems, as well as probabilistic diagnosis for dynamic domains, can be modeled in pBC+ and computed using an implementation of LPMLN.

Connected through hyperedge HE-1 (induced by source paper "strong equivalence for lpmln programs"):
  with members:
    - "weight learning in a probabilistic extension of answer set programs"
    - "computing lpmln using asp and mln solvers"
    - "logic tensor networks for semantic image interpretation"
    - "tensorlog a differentiable deductive database"
    - "probabilistic reasoning with answer sets"
    - "propositional theories are strongly equivalent to logic programs"
    - "diagnostic reasoning with a prolog"

Connected through hyperedge HE-2 (induced by source paper "bridging commonsense reasoning and probabilistic planning via a probabilistic action language"):
  with members:
    - "sdrl interpretable and data efficient deep reinforcement learningleveraging symbolic planning"
    - "robot representing and reasoning with knowledge from reinforcement learning"
    - "peorl integrating symbolic planning and hierarchical reinforcement learning for robust decision making"
    - "integrating human provided information into belief state representation using dynamic factorization"
    - "integrating task motion planning with reinforcement learning for robust decision making in mobile robots"
    - "computing lpmln using asp and mln solvers"
    - "probabilistic reasoning with answer sets"

Connected through hyperedge HE-3 (induced by source paper "elaboration tolerant representation of markov decision process via decision theoretic extension of probabilistic action language pbc"):
  with members:
    - "peorl integrating symbolic planning and hierarchical reinforcement learning for robust decision making"
    - "computing lpmln using asp and mln solvers"
    - "answer set programming for non stationary markov decision processes"
    - "probabilistic reasoning with answer sets"

Connected through hyperedge HE-4 (induced by source paper "weight learning in a probabilistic extension of answer set programs"):
  with members:
    - "inference and learning in probabilistic logic programs using weighted boolean formulas"
    - "constrained sampling and counting universal hashing meets sat solving"
    - "probabilistic inductive logic programming based on answer set programming"

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)