Page 54 - DCAP310_INTRODUCTION_TO_ARTIFICIAL_INTELLIGENCE_AND_EXPERT_SYSTEMS

Introduction to Artificial Intelligence & Expert Systems

Notes 3.4.3 Knowledge Acquisition Represented and Organized

The knowledge-acquisition process includes five major activities:
1. Knowledge Acquisition: Knowledge acquisition involves the acquisition of knowledge
from human experts, books, documents, sensors, or computer files. The knowledge may
be specific to the problem domain or to the problem-solving procedures, it may be general
knowledge (e.g., knowledge about business), or it may be meta knowledge (knowledge
about knowledge). (By meta knowledge, we mean information about how experts use
their knowledge to solve problems and about problem-solving procedures in general.)
Byrd (1995) formally verified that knowledge acquisition is the bottleneck in ES
development today; thus, much theoretical and applied research is still being conducted
in this area. An analysis of more than 90 ES applications and their knowledge acquisition
techniques and methods is available in Wagner et al. (2003).

2. Knowledge Representation: Acquired knowledge is organized so that it will be ready for
use, in an activity called knowledge representation. This activity involves preparation of
a knowledge map and encoding of the knowledge in the knowledge base.
3. Knowledge Validation: Knowledge validation (or verification) involves validating and
verifying the knowledge (e.g., by using test cases) until its quality is acceptable. Testing
results are usually shown to a domain expert(s) to verify the accuracy of the ES.
4. Inferencing: This activity involves the design of software to enable the computer to make
inferences based on the stored knowledge and the specifics of a problem. The system can
then provide advice to non-expert users.
5. Explanation and Justification: This step involves the design and programming of an
explanation capability (e.g., programming the ability to answer questions such as why a
specific piece of information is needed by the computer or how a certain conclusion was
derived by the computer).

Task 1. Create a structure for a knowledge organization.
2. Prepare and defined the neural network architecture.

Self Assessment

State whether the following statements are true or false:
10. There are six main topic areas central to knowledge acquisition that require consideration
in all ES projects.
11. Experts in the domain must not be able to communicate the details of their problem
solving methods.
12. ES should be heuristic and readily distinguishable from algorithmic programs and
databases.

13. Episodic learning refers to remembering sequences of events that we witness.
14. Relational learning is the establishment of changes within the motor system.
15. Unstructured interviews should direct the course of a meeting to accomplish specific goals
defined in advance.

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