human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent groups of papers sharing a common citing paper.

Details of the hypergraph:
Center node: "Query, PACS and simple-PAC Learning"
  Abstract: We study a distribution dependent form of PAC learning that uses probability distributions related to Kolmogorov complexity. We relate the PACS model, defined by Denis, D'Halluin and Gilleron in [3], with the standard simple-PAC model and give a general technique that subsumes the results in [3] and [6].

Connected through hyperedge HE-1 (induced by source paper "Learning DFA from Simple Examples"):
  with members:
    - "Planning and Learning in an Adversarial Robotic Game"
    - "Cryptographic Limitations on Learning Boolean Formulae and Finite Automata"

Question: Please tell me which class the center node belongs to. The 7 classes are: Neural_Networks, Reinforcement_Learning, Probabilistic_Methods, Theory, Genetic_Algorithms, Case_Based, Rule_Learning. Directly output the class name.

gpt: Theory