CSCI3406 Fuzzy Logic and Knowledge Based Systems AI

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CSCI3406 Fuzzy Logic and Knowledge Based Systems
(AI)
Knowledge Acquisition I
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Introduction

• We look at the different types of knowledge
• We identify what we mean by knowledge
  acquisition?
• The difficulties of acquiring knowledge is
  discussed.
• Key players, who affect the process, and their
  roles are identified and discussed.

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Topics of Discussion

• Knowledge acquisition.
• Difficulties in acquiring knowledge.
• Key players.

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Knowledge

• Knowledge is information of which someone is
  aware. Knowledge is also used to mean the
  confident understanding of a subject, potentially
  with the ability to use it for a specific
  purpose. (http//en.wikipedia.org/wiki/Knowledge)
  
•  Other definitions
• knowledge 'tracks the truth (Robert Nozick)
• It is suggested that our definition of knowledge
  needs to require that the believer's evidence is
  such that it logically necessitates the truth of
  the belief (Richard Kirkham)
• Knowledge is "information combined with
  experience, context, interpretation, and
  reflection. It is a high-value form of
  information that is ready to apply to decisions
  and actions." (T. Davenport et al., 1998)
• "Explicit or codified knowledge refers to
  knowledge that is transmittable in formal and
  systematic language. Tacit knowledge has a
  personal quality, which makes it hard to
  formalize and communicate." (I. Nonaka, 1994)

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Knowledge

• Explicit knowledge is referred to the knowledge
  which has been articulated, codified and stored
  in certain mediums. The most common form of
  explicit knowledge are manuals, documents,
  procedures and stories. The are also other forms
  of knowledge can be in the form of audio vision
  and other multimedia form of representations. A
  work of art and product design can be seen as yet
  another forms of explicit knowledge where human
  skills, motives and knowledge are externalized.
• Tacit Knowledge Tacit knowledge consists often
  of habits and culture that we do not recognize in
  ourselves. The tacit aspects of knowledge are
  those that cannot be codified, but can only be
  transmitted via training or gained through
  personal experience. Tacit knowledge has been
  found to be a crucial input to the innovation
  process. A nations ability to innovate depends
  on its level of tacit knowledge of how to
  innovate (conduct research, develop prototypes of
  new products processes, adapt these prototypes
  into models fit for mass-production) and of how
  to implement innovations into manufacturing,
  defense, communications, transportation, etc.

Ref http//en.wikipedia.org/
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Knowledge

• Information is data endowed with relevance and
  purpose. Converting data into information thus
  requires knowledge (Peter Drucker)
• Example to define knowledge, information and
  data How to bake a cake (Mezei, D. , 2003)
• Data - the different ingredients i.e. flour,
  water, eggs, sugar etc.
• Information - the recipe i.e. mix flour, eggs and
  water, preheat oven to 400 etc.
• Knowledge - the know how the cook uses to bake
  the cake, to best utilize the data and
  information available

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Knowledge acquisition

• Definition - The process of acquiring,
  organizing, and studying knowledge. 
•  Two main types of sources of knowledge
• Documented (which can take many forms) and
• Undocumented (usually in the expert's mind). 
• There are two types of knowledge
• shallow knowledge
• deep knowledge.

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Knowledge acquisition

• Shallow knowledge An expert has a base
  understanding of the subject, some of which could
  be described as general.  
• Example surface level information might be
  represented as If the weather is bad then stay
  in bed.

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Knowledge acquisition

• Deep Knowledge This is the knowledge that has
  been acquired by years of experience and study
  and is the detailed core of the knowledge base.
   
• Example if we take the weather example again, we
  may ask for instance what do we class as bad
  weather, why does bad weather cause us not to
  want to go out, what's so good about staying in
  bed etc. Frames  semantic networks enable us to
  represent deeper knowledge. 

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Knowledge acquisition

• Categories of Knowledge (three main ones)
• Declarative - i.e. descriptive knowledge, facts. 
• Procedural - how things are done, how to use the
  declarative knowledge. 
• Semantics - consider words symbols what they
  mean, how they are related manipulated.
  Reflects cognitive structure. 

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Difficulties of acquiring knowledge

• Why is it difficult to transfer knowledge? 
• Hard to get experts to express how they solve
  problems
• Compiling and refining all experts knowledge
• Bringing together the ideas of all those involved
  in the knowledge transfer process. 
• Representation on machine requires detailed
  expression i.e. at a very low level. Must be
  represented in a structured way.

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Key Players involved in developing an expert
system are

• Expert(s) who have the knowledge of an area being
  considered for designing a KBS for
• Knowledge Engineer(s) who collect the information
  that the client wants in the system and then put
  it all into the program in a logical way.
• Example if a client, who is an expert in cars,
  wanted a program to identify different types of
  cars, then the knowledge engineer will need to
  collect the necessary information about different
  cars and their features. It is up to the
  knowledge engineer to capture the knowledge of
  the domain expert into a knowledge base, which is
  then used to build up an expert system.
• User(s)
• Programmers
• Management

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Conclusion

• Defined what we mean by knowledge and its
  acquisition.
• Why is it difficult to acquire knowledge?
• Key players who are important in the process of
  knowledge acquisition.

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Next Steps

• Next
• Knowledge acquisition process.