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					ARTIFICIAL INTELLIGENCE


   Presentation by


                   - J.MuraliKrishna(05711A1220),
                   -J.Harikiran(05711A1213),
                    - III Year IISEM,CSIT,
                 - Narayana Engineering College.
1.      INTRODUCTION

   Artificial intelligence is the study of ideas to bring into
    being machines that respond to stimulation consist-
    -ent of with traditional responses from humans,given
    the human capacity for contemplation,judgement
    and intention.


   An AI program that models the nunaces of the
    human thought process or solves complicated real-
    world problems can be complex.
2. EXPERT SYSTEMS
3. THE ARCHITECTURE OF EXPERT
SYSTEMS
    4.KNOWLEDGE ENGINEERING



   The knowledge engineering is an applied part of AI,
    which in turn,is a part of the science of artificial
    intelligence,which in turn a part of computer science.


   A knowledge engineer interviews and opbserves and
    observes a human expert or a group of experts and
    learns what the experts know,and how they reason
    with their knowledge .
5.PROGRAMMING LANGUAGES

Some of the charecterstics of programminglanguages
for expert system are:

   Efficient mix of integer and real variables
   Good memeory-management procedures
   Extensive data manipulation routines
   Incremental complementation
   Tagged memory architecture
   Optimization of nthe System environment
   Efficient search orocedures
6.EXPERT SYSTEM SHELL
    An expert system shell is a program that provides the
     framework required for an expert system,but with no
     knowledge base.

    Types of expert systems::
1.   Decision trees
2.   Forward chaining
3.   Backward chaining
4.   State machines
5.   Bayesian networks
6.   Black board systems
7.   Case based reasoning
7.THE NEED FOR EXPERT SYSTEMSSTEMS
8.THE APPLICATIONS OFEXPERT SYSTEMS

1.   Diagnosis and troubleshooting of devices and system of
     all kinds
2.   Planning and sheduling
3.   Configuration of manufactur objects from subasseblies
4.   Financial decision making
5.   Knowledge publishing
6.   Process monitoring and control
7.   Design and manufacturing
9.BENFITS FOR EXPERT SYSTEM
10.CONCLUSION
   However a good expert system is expected to grow as it learnsfrom the user
    feedback. The dynamism of the application environment for expert systems is
    based on the individual dynamism of the components. This can be classified as
    follows:

   Most dynamic
   Moderately dynamic
   Least dynamic

   Artificial intelligence has a long way to go yet before it can achieve its goals, but
    the discoveries made by research in this area justify its continuation. There are
    intelligent techniques that have been developed though and it is doubtless that
    these will continue to be developed and similar new discoveries made. However,
    true intelligence in machines appears to be, for now at least, beyond our reach.
    Only time will tell whether this remains to be so.
    IDEAS


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posted:7/17/2011
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