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Using Control Network Programming in Teaching Randomization

Excerpt

A series of two reports are presented to this conference. The aim of the series is to demonstrate that Control Network Programming, respectively Spider, can be used as an excellent environment for teaching and learning both non-determinism and randomization. More specifically, the emphasis is on CNP implemented models and algorithms typically studied in courses on the Computation theory and Artificial intelligence for students in computing programs. While the focus of first of the reports was using CNP in teaching and learning the concept of non-determinism, the current presentation addresses probabilistic computation models and randomized algorithms.

  • Abstract
  • Keywords
  • Introduction
  • 1 Randomness
  • 2 (Lack of) Software Tools for Teaching Randomization
  • 3 CNP in Teaching Randomization
  • Implementing Randomized Models in Computation Theory and Algorithm Design
  • Teaching Randomization in Artificial Intelligence — Randomized Hill-Climbing Search Strategies
  • Teaching Randomization in Artificial Intelligence — Game Tree Evaluation
  • Conclusion
  • References

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