Rule-based Knowledge(Expert) Systems eie426-knowledge-systems-0809. ppt 2021/1/27 EIE426-AICV
2021/1/27 EIE426-AICV 1 Rule-based Knowledge (Expert) Systems eie426-knowledge-systems-0809.ppt
Contents a What is knowledge? Rules as a knowledge representation technique The main players in the development team Structure of a rule- based expert system a Characteristics of an expert system Forward chaining and backward chaining Conflict resolution What is uncertainty? Certainty factors theory and evidential reasoning 2021/1/27 EIE426-AICV
2021/1/27 EIE426-AICV 2 Contents ◼ What is knowledge? ◼ Rules as a knowledge representation technique ◼ The main players in the development team ◼ Structure of a rule-based expert system ◼ Characteristics of an expert system ◼ Forward chaining and backward chaining ◼ Conflict resolution ◼ What is uncertainty? ◼ Certainty factors theory and evidential reasoning
What is knowledge? a Knowledge is a theoretical or practical understanding of a subject or a domain Knowledge is also the sum of what is currently known, and apparently knowledge is power. Those who possess knowledge are called experts Anyone can be considered a domain expert if he or she has deep knowledge(of both facts and rules) and strong practical experience in a particular domain. The area of the domain may be limited. In general, an expert is a skilful person who can do things other people cannot 2021/1/27 EIE426-AICV
2021/1/27 EIE426-AICV 3 What is knowledge? ◼ Knowledge is a theoretical or practical understanding of a subject or a domain. Knowledge is also the sum of what is currently known, and apparently knowledge is power. Those who possess knowledge are called experts. ◼ Anyone can be considered a domain expert if he or she has deep knowledge (of both facts and rules) and strong practical experience in a particular domain. The area of the domain may be limited. In general, an expert is a skilful person who can do things other people cannot
The human mental process is internal, and it is too complex to be represented as an algorithm However, most experts are capable of expressing their knowledge in the form of rules for problem solving F the traffic light is green then the action is go F the traffic light is red then the action is stop 2021/1/27 EIE426-AICV
2021/1/27 EIE426-AICV 4 ◼ The human mental process is internal, and it is too complex to be represented as an algorithm. However, most experts are capable of expressing their knowledge in the form of rules for problem solving. IF the ‘traffic light’ is green THEN the action is go IF the ‘traffic light’ is red THEN the action is stop
Rules as a knowledge representation technique a The term rule in Al, which is the most commonly used type of knowledge representation, can be defined as an IF-then structure that relates given information or facts in the IF part to some action in the THEn part. a rule provides some description of how to solve a problem. Rules are relatively easy to create and understand Any rule consists of two parts: the IF part, called the antecedent (premise or condition) and the ThEn part called the consequent (conclusion or action) 2021/1/27 EIE426-AICV
2021/1/27 EIE426-AICV 5 Rules as a knowledge representation technique ◼ The term rule in AI, which is the most commonly used type of knowledge representation, can be defined as an IF-THEN structure that relates given information or facts in the IF part to some action in the THEN part. A rule provides some description of how to solve a problem. Rules are relatively easy to create and understand. ◼ Any rule consists of two parts: the IF part, called the antecedent (premise or condition) and the THEN part called the consequent (conclusion or action)
F THEN A rule can have multiple antecedents joined by the keywords AND (conjunction), OR (disjunction) or a combination of both F and oR And oR THEN THEN 2021/1/27 EIE426-AICV
2021/1/27 EIE426-AICV 6 IF THEN A rule can have multiple antecedents joined by the keywords AND (conjunction), OR (disjunction) or a combination of both. IF IF AND OR . . . . . . AND OR THEN THEN
The antecedent of a rule incorporates two parts: an object (linguistic object) and its value. The object and its value are linked by an operator The operator identifies the object and assigns the value Operators such as"is",are, is not,are not are used to assign a symbolic value to a linguistic object Expert systems can also use mathematical operators to define an object as numerical and assign it to the numerical value age of the customer1000 THEn ' signature of parentis required 2021/1/27 EIE426-AICV
2021/1/27 EIE426-AICV 7 ◼ The antecedent of a rule incorporates two parts: an object (linguistic object) and its value. The object and its value are linked by an operator. ◼ The operator identifies the object and assigns the value. Operators such as “is”, “are”, “is not”, “are not” are used to assign a symbolic value to a linguistic object. ◼ Expert systems can also use mathematical operators to define an object as numerical and assign it to the numerical value. IF ‘age of the customer’ 1000 THEN ‘signature of parent’ is required
Rules can represent relations, recommendations directives, strategies and heuristics Relation the fuel tank'is empty THEN the car is dead Recommendation F the season is autumn AND the sky is cloudy AND the forecast is drizzle THEN the advice is take an um brella Directive F the car is dead AND the fuel tank'is em pty THEN the action is 'refuel the car 2021/1/27 EIE426-AICV
2021/1/27 EIE426-AICV 8 Rules can represent relations, recommendations, directives, strategies and heuristics: ◼ Relation IF the ‘fuel tank’ is empty THEN the car is dead ◼ Recommendation IF the season is autumn AND the sky is cloudy AND the forecast is drizzle THEN the advice is ‘take an umbrella’ ◼ Directive IF the car is dead AND the ‘fuel tank’ is empty THEN the action is ‘refuel the car’
Strategy F the car is dead THEN the action is ' check the fuel tank step 1 is complete step 1 is complete AND the fuel tankis full THEN the action is 'check the battel step2 is complete Heuristic F the spill is liquid AND the 'spill PH<6 AND the ' spill smell is vinegar THEN the spill material is 'acetic acid 2021/1/27 EIE426-AICV
2021/1/27 EIE426-AICV 9 ◼ Strategy IF the car is dead THEN the action is ‘check the fuel tank’; step1 is complete IF step1 is complete AND the ‘fuel tank’ is full THEN the action is ‘check the battery’; step2 is complete ◼ Heuristic IF the spill is liquid AND the ‘spill PH’ <6 AND the ‘spill smell’ is vinegar THEN the ‘spill material’ is ‘acetic acid’
Example 1: ZOOKEEPER-A Deduction System To identify seven animals, a cheetah, a tiger, a giraffe, a zebra, an ostrich, a penguin, and an albatross A deduction system The then patterns specify new assertions (xx is or are yy) cheetah tt er zebra giraffe albatross, i 2021/1/27 EIE426-AICV
2021/1/27 EIE426-AICV 10 Example 1: ZOOKEEPER – A Deduction System To identify seven animals, a cheetah, a tiger, a giraffe, a zebra, an ostrich, a penguin, and an albatross. cheetah ostrich penguin zebra albatross giraffe tiger A deduction system: The then patterns specify new assertions (xx is or are yy)
