
           





         



                                      ESIE 

    
                       The Expert System Inference Engine 


                                  Novice Guide
         
         
         

         






         
         
         
         Lightwave                                        July 1986 
         P.O. Box 16858 
         Tampa, FL  33617 
         
         

         
         
                                 Copyright 1986 

                              All Rights Reserved. 

         
         
         This manual may only be distributed as one file on the ESIE 
         distribution diskette.  Such duplication and distribution is 
         authorized without compensation as long as the diskette is a 
         duplicate of the ESIE distribution diskette.  This manual may 
         also be distributed in printed form as long as a copy of the 
         distribution diskette is attached.  All other distribution is 
         strictly prohibited. 
         





























































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                               Table of Contents


         Introduction  . . . . . . . . . . . . . . . . . . . . . .  2

         What is Artificial Intelligence?  . . . . . . . . . . . .  3

         Types of Artificial Intelligence  . . . . . . . . . . . .  4
         
         Some Miscellaneous Terms  . . . . . . . . . . . . . . . .  6
         
         Where to Turn For More Information  . . . . . . . . . . .  7 









































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                                  Introduction 


         This manual is designed for the person who has absolutely no 
         experience in the field of Artificial Intelligence (AI).  
         This manual is intended to give you a working knowledge of 
         Artificial Intelligence.  When you have completed this manual 
         you should print and read the file MANUAL, which gives all 
         the details concerning ESIE. 

         We assume that you have no experience in AI whatsoever, but 
         we also assume that you are familiar with your computer.  
         Neither this manual, nor any file distributed with ESIE, will 
         try to educate you concerning your equipment.  However, 
         operation of ESIE is very straightforward and you need only 
         know the rudiments. 




































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                        What is Artificial Intelligence? 

         Now there is a good question.  Whenever a bunch of knowledge 
         engineers (KEs) get together for social hour this subject has 
         a way of rubbing us the wrong way.  In short, not even we can 
         decide on a good definition of AI.  Here is the currently 
         "accepted" view: 

              Artificial Intelligence (AI) is any action performed by 
              a machine that is normally performed by a human. 

         We at Lightwave have a little trouble with this definition.  
         First, an argument can be struck (and has been - believe us), 
         that ALL computer software fits this definition as any task 
         the computer does would probably require intelligence if a 
         person were doing the same thing.  Second, if you define 
         intelligence to mean the ability to remember facts than all 
         computers have a 200+ IQ.  Third, while we may consider 
         things like machine vision to be wonderful, they do not 
         necessarily mean intelligence. 

         Our definition of AI is a little bit different.  Although our 
         definition is not the universally accepted one, we think we 
         have heard more than one (at least two) KEs voice their 
         approval:  

              Artificial Intelligence occurs when a man-made system 
              gathers data and makes a recommendation. 

         You notice that we allow other systems besides computers to 
         be considered.  The recommendation part is key.  A system 
         that simply catalogues or computes is not AI under our 
         definition.  Also, an AI system does not have to make a 
         recommendation to a human, it can be to another system. 

         Well, enough of that.  For a working definition of AI, at 
         least until the tide changes, consider it as any activity 
         that a computer does that is human-like. 














                                                                Page 4


                        Types of Artificial Intelligence 


         If you could isolate every type of activity a human does, 
         then you probably have found all the different types of AI.  
         These are some of the most active ones in existence today: 

         Natural Language (NL) is the field where researchers are 
         trying to get machines to understand natural English, or some 
         other human language.  It is not as easy as you might think.  
         For a widely known example, the sentence "the spirit is 
         willing but the flesh is weak", was translated into "the wine 
         is agreeable but the meat is spoiled" by an NL program. 

         Machine Vision (MV) is the area where researchers are trying 
         to get machines to see.  Some of this work can be the most 
         fascinating research in the world.  We recommend it if you 
         are in the mood for a career change.  Past research has been 
         concentrating on understanding how humans see and trying to 
         duplicate that process in machines.  Now, we believe, the 
         trend is to use the special capabilities of the machine, such 
         as infrared detection and laser range finding in order to 
         give the machine vision. 

         Expert system (ES) research is the area that ESIE fits in.  
         It is involved with making the machine reason and think like 
         a human.  Although no current ES has creativity, we're sure 
         it will be classified as an ES when discovered. 
         
         Nearly all, if not all, ESs in existence today run on the 
         knowledge base principle.  In this principle, the actual 
         knowledge, or expertise, is stored in some file called the 
         knowledge base.  An Expert System Shell (ESS) is used to 
         interpret that expertise and become an instant consultant.  
         Expert systems are also receiving the most recognition from 
         industry as it has advanced enough to be useful.  

         Machine Listening (ML) works with the area of synthetic 
         speech, speech recognition and speech synthesis.  This is 
         fascinating work, and some real breakthroughs are expected 
         very soon. 

         Robotic research is primarily in the area of motor control, 
         tactile processing, and location determination.  Robotic 
         companies are increasing their sphere, however, and we are 
         sure they will soon be using all the capabilities of AI. 

         There are two typical applications in existence today where 
         expert systems are used.  One is the area of decision tree 
         applications and the other is in the area of data query. 

         In decision tree systems a knowledge base is coded into a 
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         file to provide human expertise where it might not be 
         available or to aid an expert with a second opinion for 
         better quality.  A good example of decision tree systems are 
         medical systems.  In these, a typical first question might 
         be:  "Does the patient have a fever?".  Based on the answer 
         to that question an entire area of illnesses will be 
         eliminated, and the next level of the tree will be selected. 

         Many knowledge bases today are built to run in the same 
         "inference engine."  These inference engines can use the 
         rules in a multitude of different KBs, so they are useful in 
         many tasks.  An inference engine is the computer program that 
         captures the raw inferencing power of the human mind.  It 
         uses the knowlege in the KB to act with human reasoning 
         capability. 

         The other type of knowledge based system is the data query 
         system.  In these systems, there is typically a natural 
         language front end.  This front end allows the end user to 
         query a data base in natural English commands.  The system 
         has to solve for what the end user really wants and then 
         obtain and manipulate the appropriate data.  An example of 
         this type of system is where the question might be asked: 
         "How many French speaking employess do I have?" 

         A third form of expert, or knowledge based, system involves 
         the process.  This type of ES has been largely ignored by the 
         AI community, but is starting to get large press in AI 
         journals and papers.  It is receiving notice in corporations 
         due to its low cost and quick payback period.  A process 
         based system is trying to assist a human in completing some 
         series of tasks. 

         The goal in process based systems (PBS) is to automate that 
         terribly lengthy, hard-to-read, impossible-to-use manual or 
         intruction set.  The interactive capability of PBSs are one 
         of their nice features.  ESIE can be used to build a PBS, but 
         its main intent is for decision trees, or in the mainstay of 
         AI thinking today.  In fact, when one mentions Expert System, 
         the usual mental picture is that of a decision tree system. 














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                            Some Miscellaneous Terms 
         
         
         Expert System 
         
              A computer system that has knowledge, coded as rules, 
              separate from the programs that interpret those rules.  
              These rules form some type of expertise on a subject, 
              therefore the expert system. 
         
         Inference Engine 
         
              The raw brainpower of an Expert System.  The inference 
              engine is synonymous with the brain of a child or one 
              with amnesia.  The ability to think and reason is 
              present, but the facts to think and reason with are not.  
              Also called an Expert System Shell. 
         
         Knowledge Base 
         
              A computer file that contains the knowledge that an 
              inference engine can work with.  This knowledge often 
              comes in the form of "if-then" constructs.  Such 
              constructs are called production rules, as they produce 
              some type of result when used in an inference engine. 
         
         Meta Knowledge 
         
              Knowledge that takes novel or new thought to use and 
              implement.  This knowledge is often knowledge that a 
              person would use that is not in the domain of a 
              particular problem.  For example, a mechanic's knowledge 
              that a paper clip holds things together can be used to 
              repair an automobile. 

         Declarative Knowledge 
         
              Knowledge that can be easily expressed as production 
              rules.  Expert Systems are experts at using this type of 
              knowledge. 












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                       Where to Turn For More Information 
         
         
         Your first place to turn to for help should be our technical 
         staff here at Lightwave.  There is no question too tough for 
         us to answer.  If we do not have the answer right here right 
         now then we will get it for you.  However, our technical 
         support is not free, and you will have to pay for such 
         support beforehand.  Below are a few other places you can 
         turn to for information and help: 

         In publications:
         
         
              IEEE Expert
              IEEE Computer Society
              10662 Los Vaqueros Circle
              Los Alamitos, CA  90720
              (714)821-8380


              AI Magazine
              American Association for Artificial Intelligence
              445 Burgess Drive
              Menlo Park, CA  94025
              (415)328-3123
         

         Additional public domain software or shareware:
         

              PC Softwave Interest Group
              1030 E. Duane  Suite J
              Sunnyvale, CA  94086
              (408)730-9291
         
              PC-SIG charges just enough to cover their operating 
              costs, which is more than reasonable. 


