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Introduction • Artificial intelligence: science of enabling computers to behave intelligently • Knowledge-based system (or expert system): a program which exhibits, within a specific domain, a degree of expertise in problem solving that is comparable with a human expert • expert: person with superior knowledge in some particular field, usually only obtained through experience • knowledge base: repository of expert's rules and facts about a domain • inference engine: procedure for drawing conclusions from knowledge base • knowledge engineer: develops, implements, and maintains a model of an expert's knowledge base • expert system shell: software used to implement an expert system; usually generic (and commercialized) B. Ross Cosc 4f79 1 Terms (cont) • heuristics: methods of findings solutions so as to promote efficiency - inference engine typically employs domain-specific heuristics so that solutions can be found reasonably fast • fact: simple assertion of a truth eg. mother (jane, john). • rule: a conditional or causal relationship eg. if is_a_tiger then not(pet) • meta-rule: a rule that describes a rule , part of a theory of knowledge eg. if true_examples_exist(rule) and no_counter_examples(rule) then universal_truth(rule) B. Ross Cosc 4f79 2 Nature of knowledge (Hall) "common sense" Informal Technical mathematical, algorithmic B. Ross Cosc 4f79 Formal domain-specific rules 3 Knowledge (cont) • technical vs. formal: - both can be formalized - technical: theory remain same, data changes eg. mathematical formulae, programs formal: rules change, ie. rules are data • knowledge-based systems are concerned with processing formal knowledge - can employ technical knowledge to help • note: formalizing informal knowledge is a major focus of AI research in machine learning B. Ross Cosc 4f79 4 Structure of a KBS Knowledge Base Inference Engine I n t e r f a c e "Real world" ( humans, robots, machines, ... ) Working Storage B. Ross Cosc 4f79 5 Expert Systems vs. conventional programs Similarities • both programmed in a programming language • design processes are similar Design Prototype Test Production Revise • both get "bugs" Differences • KBS uses knowledge base with domain rules • KBS uses (domain-dependent) heuristics B. Ross Cosc 4f79 6 (cont) • expert systems have an explanation facility • expert systems may have a learning component * design & implementation of KBS requires knowledge engineering, and use of expert knowledge - uncertain and probabilistic knowledge - conflicting knowledge - unknown B. Ross Cosc 4f79 7 Conventional pgms vs Ex.Sys Conventional programs Expert Systems • • • Numeric Algorithmic Info & control integrated • • • Difficult to modify Precise info Command interface • Final result given • Optimal solution Symbolic Heuristic Knowledge & control separated Easier to modify Uncertain info Natural dialog w. explanation Recommendation(s) w. expl Acceptable solution(s) B. Ross Cosc 4f79 8 Why use expert systems? • expertise often required in complex human activities • expertise is expensive and rare • level of expertise can vary widely • experience in a field is difficult to easily obtain • Expert systems: - are relatively cheap - are consistent, objective, and not prone to stress B. Ross Cosc 4f79 9 Some application areas... • finances: financial planning, stock market, tax preparation, banking, ... • law: interpretation of legal text, legal inferences • medicine: diagnosis and treatment • scientific: chemistry • engineering: machine monitoring and control • robotics • weather forecasting B. Ross Cosc 4f79 10