This document outlines a research paper on real-time knowledge-based systems (RTKBS). It includes an abstract that states the goal is to develop a system that can meet cognitive needs and reduce cognitive load. It then defines key terms like cognitive load and discusses why RTKBS are useful. The document lists challenges for RTKBS, potential applications, and summarizes survey results on tools and methods. It also outlines limitations and opportunities for future research, and concludes that developing intelligent real-time systems is more difficult than traditional expert systems.

2. KNOWLEDGE BASED AGENTS IN
REAL TIME
Members:
• Ghulam Murtaza
• Zain-ul-Hasaanat
• Muhammad Zubair
• Nadeem Shahzad
• Junaid Shabbir
• Waseem Mehmood

3. Table of Contents
• Abstract (Problem Statement)
– Some important definitions
• Characteristics of RTKBS’s
– Challenges for RTKBS’s*
– RTLBS’s Applications Survey
• Methodologies (Tools)
• Survey Results
• Limitations
• Future Research
• Conclusion
• Appendix
• Bibliography
• References
• Q/A . . ?
Keywords: *RTKBS’s – ( Real Time Knowledge Based Systems)

4. Abstract
This paper is about Real time expert system.
Problem Statement:
“Our system must me expert enough to meet the
needs of cognitive science to remove cognitive
load."
Keywords: *cognitive load

5. * Cognitive Load
The level of effort associated with thinking
and reasoning including perception, memory,
language, etc.

6. Why Real Time Expert System ?
“Principal reason for using a real-time expert
system is to reduce the cognitive load on users
or to enable them to increase their
productivity without the cognitive load on
them increasing.“
{A formal definition by: Turner (1986)}

7. Human-System Interaction
(Causes)
A real-time expert system might be appropriate,
especially when:
1Conventional techniques have failed or are
impractical, include problem-solving situations
where humans suffer from cognitive overload.
2Fail to effectively monitor all available
information.
3Unable to resolve conflicting constraints, are
expensive(which cause high expense) and work
force etc.

8. Real Time (definition)
The common definition of real time are:
"perceptually fast" or, at least, "faster than a
human can do it."
A better definition of real time states that:
"the system responds to incoming data at a
rate as fast or faster than it is arriving."

9. What is a knowledge-based system?
A system which is built around a knowledge base.
i.e. a collection of knowledge, taken from a
human, and stored in such a way that the system
can reason* with it.
Keywords: *reason-( Respond Automatically)

10. Challenges for RTKBS’s
• Non monotonicity.
• Continuous operation.
• Asynchronous events.
• Interface to external environment.
• Uncertain or missing data.
• High performance.
• Temporal reasoning.
• Guaranteed response times.

11. RTKBS’s Applications
Survey’s
• Aerospace
• Communication
• Medical
• Process Control
• Robotics

17. Survey Results
The survey results are grouped into
applications, tools, and theory.

18. Real-TimeExpert System Tools
• Expert Controller
UME Corporation of Larkspur,
California, sells a tool called
Expert Controller. It is a shell
and a processor box that has
two RS-232 ports for direct
interface to programmable
logic controllers which
monitor and control an
application.
Figure: Expert Controller

19. Real-TimeExpert System Tools
• Activation Framework (AF)
AF is a software framework written in C that
supports the implementation of real-time AI
programs on multiple interconnected
computers.
• Forth
Forth offers significant advantages over
other languages in speed and compactness.

20. Real-TimeExpert System Tools List
• G2
• XNET
• Fuzzy Inference Chip.
• ONSPEC Superintendent
• Blackboard Objects (BLOBS)
• The Process Diagnostic System (PDS)
• The Process Intelligent Control (PICON)
• The Procedural Reasoning System (PRS)
• The Hybrid Expert System Controller (Hexscon)
• The Real Time Expert System Club of Users (RESCU)
• The Yorktown Expert System Language One (YES/L1)

21. Limitations
In real-time problem solving, many human
based limitations are:
- To overlook relevant information
- To respond inconsistently
- To respond too slowly
These are most apparent Limitations, and the
need to overcome these short comings is at
its greatest.

22. Future Research
Real-time domains present a new and
challenging environment for the application of
knowledge-based problem-solving techniques.
However, a substantial amount of research is
still needed to solve many difficult problems
before real time expert systems can enhance
current monitoring and control systems.

23. Conclusions
From the results of the survey, we see that
considerable effort is being put into
developing intelligent real-time systems, a
much more difficult area than has traditionally
been approached using expert systems.

24. References
• All the data is collected from given Research
paper.
• Some definitions are collected from
Wikipedia.

25. Any Questions. . ?