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: "A Computer Scientist's View of Life, the Universe, and Everything"
  Abstract: Is the universe computable? If so, it may be much cheaper in terms of information requirements to compute all computable universes instead of just ours. I apply basic concepts of Kolmogorov complexity theory to the set of possible universes, and chat about perceived and true randomness, life, generalization, and learning in a given universe. Assumptions. A long time ago, the Great Programmer wrote a program that runs all possible universes on His Big Computer. "Possible" means "computable": (1) Each universe evolves on a discrete time scale. (2) Any universe's state at a given time is describable by a finite number of bits. One of the many universes is ours, despite some who evolved in it and claim it is incomputable. Computable universes. Let T M denote an arbitrary universal Turing machine with unidirectional output tape. T M 's input and output symbols are "0", "1", and "," (comma). T M 's possible input programs can be ordered alphabetically: "" (empty program), "0", "1", ",", "00", "01", "0,", "10", "11", "1,", ",0", ",1", ",,", "000", etc. Let A k denote T M 's k-th program in this list. Its output will be a finite or infinite string over the alphabet f "0","1",","g. This sequence of bitstrings separated by commas will be interpreted as the evolution E k of universe U k . If E k includes at least one comma, then let U l k represents U k 's state at the l-th time step of E k (k; l 2 f1; 2; : : : ; g). E k is represented by the sequence U 1 k corresponds to U k 's big bang. Different algorithms may compute the same universe. Some universes are finite (those whose programs cease producing outputs at some point), others are not. I don't know about ours. TM not important. The choice of the Turing machine is not important. This is due to the compiler theorem: for each universal Turing machine C there exists a constant prefix C 2 f "0","1",","g fl such that for all possible programs p, C's output in response to program C p is identical to T M 's output in response to p. The prefix C is the compiler that compiles programs for T M into equivalent programs for C. k denote the l-th (possibly empty) bitstring before the l-th comma. U l

Connected through hyperedge HE-1 (induced by source paper "DISCOVERING NEURAL NETS WITH LOW KOLMOGOROV COMPLEXITY AND HIGH GENERALIZATION CAPABILITY Neural Networks 10(5):857-873, 1997"):
  with members:
    - "ENVIRONMENT-INDEPENDENT REINFORCEMENT ACCELERATION  difference between time and space is that you can't reuse time."
    - "FLAT MINIMA Neural Computation 9(1):1-42 (1997)"
    - "ON LEARNING HOW TO LEARN LEARNING STRATEGIES"
    - "Learning Team Strategies With Multiple Policy-Sharing Agents: A Soccer Case Study"
    - "GUESSING CAN OUTPERFORM MANY LONG TIME LAG ALGORITHMS"

Connected through hyperedge HE-2 (induced by source paper "REINFORCEMENT LEARNING WITH SELF-MODIFYING POLICIES"):
  with members:
    (none)

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: Reinforcement_Learning