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 "Building Intelligent Agents for Web-Based Tasks: A Theory-Refinement Approach"):
  Abstract: We present and evaluate an infrastructure with which to rapidly and easily build intelligent software agents for Web-based tasks. Our design is centered around two basic functions: ScoreThis-Link and ScoreThisPage. If given highly accurate such functions, standard heuristic search would lead to efficient retrieval of useful information. Our approach allows users to tailor our system's behavior by providing approximate advice about the above functions. This advice is mapped into neural network implementations of the two functions. Subsequent reinforcements from the Web (e.g., dead links) and any ratings of retrieved pages that the user wishes to provide are, respectively, used to refine the link- and page-scoring functions. Hence, our agent architecture provides an appealing middle ground between nonadaptive "agent" programming languages and systems that solely learn user preferences from the user's ratings of pages. We present a case study where we provide some simple advice and specialize our general-purpose system into a "home-page finder". An empirical study demonstrates that our approach leads to a more effective home-page finder than that of a leading commercial Web search engine.

Includes members:
  Member "Machine Learning Learning to Predict by the Methods of Temporal Differences Keywords: Incremental learning, prediction,":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "TDLeaf(): Combining Temporal Difference learning with game-tree search.")
  Member "Theory Refinement Combining Analytical and Empirical Methods":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Automated Refinement of First-Order Horn-Clause Domain Theories")
  Member "Machine Learning,  Creating Advice-Taking Reinforcement Learners":
    also connected through other hyperedges:
      (none)

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: Neural_Networks