Page 175 - DCAP506_ARTIFICIAL_INTELLIGENCE

Unit 12: Learning

 In discovery learning, the learner utilizes his own experience and prior knowledge to Notes
learn the truths that are to be studied.

12.14 Keywords

Classification: It is the procedure of allocating, to a specific input, the name of a class to which
it associates.
Explanation-based Learning (EBL): An Explanation-based Learning (EBL) system accepts an
example (i.e. a training example) and illustrates what it learns from the example.
Induction: The thought of generating a classification program that can develop its own class
definitions is known as concept learning or induction.

Learning: Learning is defined as modifications in the system that are adaptive in the sense that
they facilitate the system to do the similar task or tasks taken from the similar population more
competently and more successfully the next time.
Rote Learning: Rote learning is the fundamental learning activity which is also known as
memorization since the knowledge, without any alteration is, just copied into the knowledge
base.
Winston’s Learning Program: It is an early structural concept learning program which functions
in a simple blocks world domain.

12.15 Review Questions

1. What is rote learning? Illustrate with example.
2. Enlighten some issues that are relevant to more complex learning issues.

3. Discuss the process of Learning by taking Advice. Give example.
4. Explicate the process of induction with example.
5. What is Winston’s Learning Program? Illustrate the basic approach of Winston’s Program.
6. What is the main goal of version spaces? Explain with the help of algorithm.
7. To categorize a specific input, we begin at the top of the tree and reply questions until we
reach a leaf, where the specification is stored. Comment.
8. Describe the concept of Explanation-based Learning (EBL).
9. Make distinction between learning with macro-operators and learning by chunking.

10. What is a cluster? Illustrate the process of beginning clustering.

Answers: Self Assessment

1. Learning 2. Generalization
3. Rote Learning 4. Memorization
5. Operational 6. Concept Learning or Induction

7. Version Spaces 8. Explanation-based Learning (EBL)
9. PRODIGY 10. Parameter Adjustment
11. Macro-operators 12. Constants

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