human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge groups papers that share a common citing paper.

Details of the hypergraph:
Center hyperedge (induced by source paper "Price's Theorem and the MAX Problem"):
  Abstract: We present a detailed analysis of the evolution of GP populations using the problem of finding a program which returns the maximum possible value for a given terminal and function set and a depth limit on the program tree (known as the MAX problem). We confirm the basic message of [ Gathercole and Ross, 1996 ] that crossover together with program size restrictions can be responsible for premature convergence to a sub-optimal solution. We show that this can happen even when the population retains a high level of variety and show that in many cases evolution from the sub-optimal solution to the solution is possible if sufficient time is allowed. In both cases theoretical models are presented and compared with actual runs. Experimental evidence is presented that Price's Covariance and Selection Theorem can be applied to GP populations and the practical effect of program size restrictions are noted. Finally we show that covariance between gene frequency and fitness in the first few generations can be used to predict the course of GP runs.

Includes members:
  Member "The Troubling Aspects of a Building Block Hypothesis for Genetic Programming":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Genetic Programming Exploratory Power and the Discovery of Functions")
  Member "The Schema Theorem and Price's Theorem":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Evolution in Time and Space The Parallel Genetic Algorithm")
  Member "Genetic Programming with One-Point Crossover and Point Mutation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "An Experimental Analysis of Schema Creation, Propagation and Disruption in Genetic Programming")

Question: Please tell me which class the citing paper (i.e., the source paper of the center hyperedge) 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: Genetic_Algorithms