Model-based Reasoning

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● CHAPTER 13
● Reasoning in
Artificial Intelligence
● How People Reason and
Solve Problems
● Reasoning Methods
● Reasoning with Logic
● Inferencing with Rules: Forward and Backward Chaining
● Forward and Backward Chaining
● Backward Chaining
● Forward Chaining
● The Inference Tree
● Inferencing with Frames
● Model-based Reasoning
● Case-based Reasoning (CBR)
● Finding Relevant Cases Involves:
● What is a Case?
● Case-based Reasoning Process
(Figure 13.4)
● CBR Uses, Issues and Applications
● CBR Issues and Questions
● Pay-TV Help Desk
CBR Application Example
● CBR Construction –
Special Tools – Examples
● Explanation and
Metaknowledge
● Explanation Purposes
● Rule Tracing Technique
● Two Basic Explanations
● Other Explanations
● Metaknowledge
● Generating Explanations
● Typology of ES Explanations
● Inferencing with Uncertainty
● Representing Uncertainty
● Numeric Uncertainty Representation
● Graphic and Influence Diagrams
● Symbolic Representation of
Uncertainty
● Probabilities and
Related Approaches
● Several Approaches for
Combining Probabilities
● The Bayesian Extension
● Two Major Deficiencies
● Dempster-Shafer Theory of Evidence
● Theory of Certainty (Certainty Factors)
● Belief and Disbelief
● Combining Certainty Factors
● AND
● OR
● Combining Two or More Rules
● Assume an independent relationship between the rules

نوع زبان: انگلیسی حجم: 0.13 مگا بایت
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system, decision, support, upper, hall, jay, e., river, saddle, ed, turban, copyright,

توجه: این مطلب در تاریخ 2019/06/07 12:49:15 به صورت خودکار از فضای وب آشکار توسط موتور جستجوی پاورپوینت جمع آوری شده است و در صورت اعلام عدم رضایت تهیه کننده ی آن، طبق قوانین سایت از روی وب گاه حذف خواهد شد. این مطلب از وب سایت زیر استخراج شده است و مسئولیت انتشار آن با منبع اصلی است.

http://www.indiana.edu/~bnwrbk/K510/ch13.ppt

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chapter ۱۳ inference techniques decision support systems and intelligent systems efraim turban and jay e. aronson ۶th ed copyright ۲ ۱ prentice hall upper saddle river nj reasoning in artificial intelligence knowledge must be processed reasoned with computer program accesses knowledge for inferencing inference engine or control program rule interpreter in rule based systems directs search through the knowledge base decision support systems and intelligent systems efraim turban and jay e. aronson ۶th ed copyright ۲ ۱ prentice hall upper saddle river nj how people reason and solve problems sources of power formal methods logical deduction heuristic reasoning if then rules focus common sense related toward more or less specific goals divide and conquer parallelism decision support systems and intelligent systems efraim turban and jay e. aronson ۶th ed copyright ۲ ۱ prentice hall upper saddle river nj representation analogy synergy serendipity luck lenat ۱۹۸۲ sources of power translated to specific reasoning or inference methods table ۱۳.۱ decision support systems and intelligent systems efraim turban and jay e. aronson ۶th ed copyright ۲ ۱ prentice hall upper saddle river nj reasoning methods deductive reasoning inductive reasoning analogical reasoning formal reasoning procedural numeric reasoning metalevel reasoning decision support systems and intelligent systems efraim turban and jay e. aronson ۶th ed copyright ۲ ۱ prentice hall upper saddle river nj reasoning with logic modus ponens if a then b a and a  b  b a and a  b are propositions in a knowledge base modus tollens when b is known to be false resolution combines substitution modus ponens and other logical syllogisms decision support systems and intelligent systems efraim turban and jay e. aronson ۶th ed copyright ۲ ۱ prentice hall upper saddle river nj inferencing with rules forward and backward chaining firing a rule when all of the rule s hypotheses the if parts are satisfied can check every rule in the knowledge base in a forward or backward direction continues until no more rules can fire or until a goal is achieved decision support systems and intelligent systems efraim turban and jay e. aronson ۶th ed copyright ۲ ۱ prentice hall upper saddle river nj forward and backward chaining chaining linking a set of pertinent rules search process directed by a rule interpreter approach forward chaining if the premise clauses match the situation then the process attempts to assert the conclusion backward chaining if the current goal is to determine the correct conclusion then the process attempts to determine whether the premise clauses facts match the situation decision support systems and intelligent systems efraim turban and jay e. aronson ۶th ed copyright ۲ ۱ prentice hall upper saddle river nj backward chaining goal driven start from a potential conclusion hypothesis then seek evidence that supports or contradicts it often involves formulating and testing intermediate hypotheses or subhypotheses decision support systems and intelligent systems efraim turban and jay e. aronson ۶th ed copyright ۲ ۱ prentice hall upper saddle river nj forward chaining data driven start from available information as it becomes available then try to draw conclusions what to use if all facts available up front as in auditing forward chaining diagnostic problems backward chaining decision support systems and intelligent systems efraim turban and jay e. aronson ۶th ed copyright ۲ ۱ prentice hall upper saddle river nj the inference tree goal tree or logical tree schematic view of the inference process similar to a decision tree figure ۱۳.۳ inferencing tree traversal advantage guide for the why and how explanations decision support systems and intelligent systems efraim turban and jay e. aronson ۶th ed copyright ۲ ۱ prentice hall upper saddle river nj inferencing with frames much more complicated than reasoning with rules slot provides for expectation driven processing empty slots can be filled with data that confirm expectations look for confirmation of expectations often involves filling in slot values can use rules in frames hierarchical reasoning decision support systems and intelligent systems efraim turban and jay e. aronson ۶th ed copyright ۲ ۱ prentice hall upper saddle river nj model based reasoning based on knowledge of structure and behavior of the devices the system is designed to understand especially useful in diagnosing difficult equipment problems can overcome some of the difficulties of rule based es systems include a deep knowledge model of the device to be diagnosed that is then used to identify the cause s of the equipment s failure reasons from first principles common sense often combined with other representation and inferencing methods decision support systems and intelligent systems efraim turban and jay e. aronson ۶th ed copyright ۲ ۱ prentice hall upper saddle river nj model based es tend to be transportable simulates the structure and function of the machinery being diagnosed models can be either mathematical or component necessary condition is the creation of a complete and accurate model of the system under study especially useful in real time systems decision support systems and intelligent systems efraim turban and jay e. aronson ۶th ed copyright ۲ ۱ prentice hall upper saddle river nj case based reasoning cbr adapt solutions used to solve old problems for new problems variation rule induction method chap. ۱۳ but cbr finds cases that solved problems similar to the current one and adapts the previous solution or solutions to fit the current problem while considering any difference between the two situations decision support systems and intelligent systems efraim turban and jay e. aronson ۶th ed copyright ۲ ۱ prentice hall upper saddle river nj finding relevant cases involves characterizing the input problem by assigning appropriate features to it retrieving the cases with those features picking the case s that best match the input best extremely effective in complex cases justification human thinking does not use logic or reasoning from first principle process the right information retrieved at the right time central problem identification of pertinent information whenever needed use scripts decision support systems and intelligent systems efraim turban and jay e. aronson ۶th ed copyright ۲ ۱ prentice hall upper saddle river nj what is a case case defines a problem in natural language descriptions and answers to questions and associates with each situation a proper business action scripts describe a well known …

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