Expert systems are intelligent computer programs that mimic the problem-solving abilities of human experts, performing tasks such as diagnosing diseases and financial forecasting. They consist of components like a knowledge base, inference engine, and user interface, designed to replace or assist human expertise, especially in areas with scarce human resources. While they enhance decision-making and data utilization, expert systems face limitations such as narrow problem scope and maintenance challenges.

1. Expert Systems
Kiran Paul

2. EXPERT SYSTEM
Expert system are intelligent computer
programs designed to stimulate the problem-solving
behavior of human experts.
These programs perform a task that would
otherwise be performed by a human expert.
It create a tool that can be used by a layman
to solve difficult or ambiguous problems.

3. There are expert systems that can be diagnose
human illnesses, make financial forecast, and
schedule routes for delivery vehicles.
They also play chess, underwrite insurance policies,
and perform many services which previously required
human expertise.
Some expert systems are designed to take the place
of human experts, While others are designed to aid
them.

4. DEFINITION
“An expert system is an interactive computer-based
decision tool that uses both facts and heuristics to solve
difficult decision problems based on knowledge acquired
from an expert.”
An expert system compared with traditional computer :
Inference engine + Knowledge = Expert system

5. CHARACTERISTICS
EXPERTISE
SYMBOL MANIPULATION
INTELLIGENCE
COMPLEXITY
REFORMULATION
REASONING ABOUT SELF
TYPE OF TASK

6. KINDS OF EXPERT SYSTEMS
Advice expert system
Decision-support expert system
Intelligent interfaces
Learning systems

7. COMPONENTS OF EXPERT SYSTEM
Knowledge base
Inference engine
User interface

8. In addition to above components,
Working memory
Domain expert
Explanation capacity
A knowledge maintenance module to update the
knowledge base.
An interface to other systems, such as database
management and spreadsheets etc.

9. Components of Expert System
User Interface
Inference
Engine
Knowledge
Base
Working
Storage
User
System
Engineer
Domain
Expert
Expertise
Knowledge
Engineer
Encoded
Expertise

10. NEED OF EXPERT SYSTEM?
Human expertise is very scarce.
Humans get tired from physical or mental
workload.
Humans forget crucial details of a problem.
Humans are inconsistent in their day-to-day
decisions.
Humans have limited working memory.
Humans are unable to comprehend large
amounts of data quickly.

11. Humans are unable to retain large amounts
of data in memory.
Humans are slow in recalling information
stored in memory.
Humans are subject to deliberate or
inadvertent bias in their actions.
Humans can deliberately avoid decision
responsibilities.
Humans lie, hide, and die.

12. WHERE EXPERT SYSTEM ARE MOST
EFFECTIVE?
Decision Support
Problem-Solving Diagnostics
Data Analysis
Advisory System
Background Monitoring
Inconsistency Detection
Smart Questionnaires
Application in Agriculture

13. Diagnosis diseases of wheat
symptoms - recommendations.
Problem in leaves- disease may be
Stem rust(h1)
Problem in leaves- disease may be Flag
smut (h0)

14. The developmental process then adds
additional information to help determine
whether the hypothesis “disease is flag
smut on leaves” is true.

15. This is not as simple as it might look as
other considerations include
symptoms appeared on the defected
parts including size of patches
color of spots
condition of defected organ and other
information.

16. The representation of flag smut disease is
mentioned below.
• RULE [Is it going to find the problem
area which is flag smut?]
• If [season] = "spring" and
• [stage]="early" and
• [problem_is_in]="leaves" and
• [leave_part]="upper" and
• [strip_color]="light_green_to_grey_black

17. Then [the problem] = "FALG
SMUT IS DIAGNOSED"
• [recommendation 1]= "CAUSAL
ORGANISM: Urocystic tritici" and
• [recommendation 2]=
"PERPETUATION: The disease is
perpetuated through seed borne and/or
soil borne spores, which can survive in
the soil up to a period of three years"
and
• [

18. • recommendation 3]= "MANAGEMENT:
1. GROW RESISTANT CULTIVARS.
5. EARLY PLANTING
6. USING THE WET METHOD OF
SOWING. IRRIGATING JUST AFTER
SOWING.
7. ROGUE OUT AND BURN THE
INFECTED PLANT. "

19. Starting consultation

20. Problem classification

21. season

22. EXPERT SYSTEM IN AGRICULTURE
AMRAPALIKA: An expert system for the diagnosis of
pests, diseases and disorders in Indian mango.
Dr. Wheat: A Web-based expert system for diagnosis
of diseases and pests in Pakistani wheat.

23. BENEFITS OF EXPERT SYSTEMS
Increase the probability, frequency, and
consistency of making good decisions.
Help distribute human expertise.
Facilitate real-time, low-cost expert level
decisions by the non expert.
Enhance the utilization of most of the
available data.

24. Permit objectivity by weighing evidence without bias
and without regard for the user’s personal and
emotional reactions.
Permit dynamism through modularity of structure.
Free up the mind and time of the human expert to
enable him or her to concentrate on more creative
activities.
Encourage investigations into the subtle areas of a
problem.

25. LIMITATIONS OF EXPERT SYSTEMS
Not widely used or tested.
Limited to relatively narrow problems.
No “common sense”.
Cannot readily deal with “mixed” knowledge.
Possibility of error.
Cannot refine own knowledge base.
Difficult to maintain.
System are not always up to date.
May have high development costs

26. Conclusion
An expert system is a powerful tool with
extensive potential in various field.
The development of an expert system
requires the combined effort of specialists
from many fields of different areas and can
only be accomplished with the cooperation of
the users and advisors who will use them.