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ARTIFICIAL INTELLIGENCE [INTELLIGENT AGENTS PARADIGM] Professor Janis Grundspenkis Riga Technical University Faculty of Computer Science and Information.

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Presentation on theme: "ARTIFICIAL INTELLIGENCE [INTELLIGENT AGENTS PARADIGM] Professor Janis Grundspenkis Riga Technical University Faculty of Computer Science and Information."— Presentation transcript:

1 ARTIFICIAL INTELLIGENCE [INTELLIGENT AGENTS PARADIGM] Professor Janis Grundspenkis Riga Technical University Faculty of Computer Science and Information Technology Institute of Applied Computer Systems Department of Systems Theory and Design E-mail: Janis.Grundspenkis@rtu.lv RULE-BASED EXPERT SYSTEMS

2 Rule-Based Expert Systems Rule-based expert systems represent problem-solving knowledge as IF...THEN... rules. There is one-to-one-mapping of the implication  to the corresponding IF...THEN... rule.

3 Rule-Based Expert Systems For example, “If sun shines then weather is fine” Knowledge representation in first-order logic: A - ”sun shines” B - ”weather is fine” A  B Knowledge representation as IF...THEN... rule: IF sun shines THEN weather is fine

4 Rule-Based Expert Systems The architecture of rule-based expert systems corresponds to the production system model. A production system is defined by: 1.The set of production rules (productions) 2.Working memory 3.The recognize-act cycle

5 Rule-Based Expert Systems A production is a condition-action pair. The condition part of the rule is IF pattern that determines which rule may be applied. The action part of the rule is THEN pattern that defines the associated problem-solving step.

6 Rule-Based Expert Systems WORKING MEMORY Working memory contains a description of the current state of the world in a reasoning process. The description of the current state of the world is matched against the IF pattern of a production to select appropriate problem- solving actions. THEN patterns alter the contents of working memory.

7 Rule-Based Expert Systems THE RECOGNIZE-ACT CYCLE Working memory is initialized with the beginning problem description. The current state of the problem-solving is maintained as a set of patterns in working memory. These patterns are matched against the IF patterns of the production rules; this produces a subset of the production rules, called the conflict set, whose conditions match IF patterns in working memory.

8 Rule-Based Expert Systems THE RECOGNIZE-ACT CYCLE (continued) Conflict resolution chooses a rule from the conflict set for firing. To fire a rule, its action is performed, changing the contents of working memory (THEN pattern is added to the working memory). The process terminates when the contents of working memory do not match any rule condition.

9 Rule-Based Expert Systems A PRODUCTION SYSTEM Production Rules IF pattern THEN pattern Working Memory Pattern Knowledge Base

10 Rule-Based Expert Systems EXPERT SYSTEM FOR DIAGNOSING AUTOMOTIVE PROBLEMS Knowledge Base Rule 1:IF the engine is getting gas AND engine will turn over THEN the problem is spark plugs Rule 2:IF the engine does not turn over AND the lights do not come on THEN the problem is battery or cables

11 Rule-Based Expert Systems EXPERT SYSTEM FOR DIAGNOSING AUTOMOTIVE PROBLEMS (continued) Rule 3:IF the engine does not turn over AND the lights do come on THEN the problem is starter motor Rule 4:IF there is gas in the fuel tank AND there is gas in the carburator THEN the engine is getting gas


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