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 "Evolving Visual Routines"):
  Abstract: Traditional machine vision assumes that the vision system recovers a a complete, labeled description of the world [ Marr, 1982 ] . Recently, several researchers have criticized this model and proposed an alternative model which considers perception as a distributed collection of task-specific, task-driven visual routines [ Aloimonos, 1993, Ullman, 1987 ] . Some of these researchers have argued that in natural living systems these visual routines are the product of natural selection [ Ramachandran, 1985 ] . So far, researchers have hand-coded task-specific visual routines for actual implementations (e.g. [ Chapman, 1993 ] ). In this paper we propose an alternative approach in which visual routines for simple tasks are evolved using an artificial evolution approach. We present results from a series of runs on actual camera images, in which simple routines were evolved using Genetic Programming techniques [ Koza, 1992 ] . The results obtained are promising: the evolved routines are able to correctly classify up to 93% of the images, which is better than the best algorithm we were able to write by hand.

Includes members:
  Member "Evolution of Pseudo-colouring Algorithms for Image Enhancement with Interactive Genetic Programming":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "4 Implementing Application Specific Routines  Genetic algorithms in search, optimization, and machine learning. Reading, MA: Addison-Wesley.")
  Member "Evolving Visually Guided Robots":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Issues in Evolutionary Robotics")
  Member "Evolution, Learning, and Instinct: 100 Years of the Baldwin Effect Using Learning to Facilitate the":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Data Analyses Using Simulated Breeding and Inductive Learning Methods")
  Member "Generality versus Size in Genetic Programming":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "Evolving a Generalised Behaviour: Artificial Ant Problem Revisited")
  Member "Evolving Edge Detectors with Genetic Programming edge detectors for 1-D signals and image profiles. The":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "1 GP-COM: A Distributed, Component-Based Genetic Programming System in C++")

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