Chapter 11 Artificial Intelligence and Expert Systems

Chapter 11IS for Management2 Artificial Intelligence (AI) The ability to mimic or duplicate the functions of the human brain AI Systems: The people, procedures, hardware, software, data, telecommunications, & knowledge needed to develop computer systems & machines that demonstrate the characteristics of intelligence

Chapter 11IS for Management3 Intelligent Behavior Learn from experience Apply knowledge acquired from experience Handle complex situations Solve problems when important information is missing Determine what is important React quickly & correctly to a new situation Understand visual images Process & manipulate symbols Be creative & imaginative Use heuristics

Chapter 11IS for Management4 Major Branches of AI (Figure 11.2)

Chapter 11IS for Management5 Expert Systems Can explain their reasoning or suggested decisions Can display intelligent behavior Can draw conclusions from complex relationships Can provide portable knowledge Expert System Shell: A collection of software packages & tools used to develop expert systems

Chapter 11IS for Management6 Limitations of Expert Systems Not widely used or tested Limited to relatively narrow problems Cannot readily deal with “mixed” knowledge Possibility of error Cannot refine own knowledge base Difficult to maintain May have high development costs Raise legal & ethical concerns

Chapter 11IS for Management7 Expert Systems’ Capabilities (Figure 11.5) Explore impact of strategic goals Impact of plans on resources Integrate general design principles & manufacturing limitations Provide advise on decisions Monitor quality & assist in finding solutions Look for causes & suggest solutions

Chapter 11IS for Management8 When to Use Expert Systems Provide a high potential payoff or significantly reduced downside risk Capture & preserve irreplaceable human expertise Provide needed expertise (consistently) at a number of locations at the same time or in a hostile environment that is dangerous to human health Provide expertise that is expensive or rare Develop a solution faster than human experts can Provide expertise needed for training & development to share the wisdom of human experts with a large number of people

Chapter 11IS for Management9 Expert Systems’ Components (Figure 11.7)

Chapter 11IS for Management10 More Definitions Fuzzy Logic: Mathematics/computer science area that allows shades of gray & does not require everything to be simply yes/no, or true/false Rule: A conditional statement that links given conditions to actions or outcomes Backward Chaining: A method of reasoning that starts with conclusions & works backward to the supporting facts (deductive) Forward Chaining: A method of reasoning that starts with the facts & works forward to the conclusions (inductive)

Chapter 11IS for Management11 Yet More Definitions Explanation Facility: Allows a user or decision maker to understand how the expert system arrived at its conclusions/results Knowledge Acquisition Facility: Provides a convenient, efficient means of capturing & storing the components of the knowledge base Domain: The limited area of knowledge addressed by the expert system

Chapter 11IS for Management12 Expert Systems Development (Figure 11.10)

Chapter 11IS for Management13 Participants in Expert Systems Development & Use (Figure 11.11)

Chapter 11IS for Management14 Evolution of Expert Systems Software (Figure 11.12)

Chapter 11IS for Management15 Advantages of Expert Systems Easy to develop and modify The use of satisficing The use of heuristics Development by knowledge engineers & users

Chapter 11IS for Management16 Expert Systems Development Alternatives (Figure 11.13)

Chapter 11IS for Management17 Applications of Expert Systems & AI Granting credit Information management & retrieval AI & expert systems embedded in products Plant/facility layout Hospitals & medical facilities, including diagnostic tools Help desks & assistance Employee performance evaluation Loan analysis Virus detection Repair & maintenance Shipping Marketing Warehouse optimization

Chapter 11IS for Management18 Chapter 11 Case Use of fuzzy logic to predict length of patient hospital stay, page 514