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Define artificial intelligence, and explain how AI technologies support decision making Describe an expert system, its applications, and its components Describe case-based reasoning Summarize the types of intelligent agents and how they are used Describe fuzzy logic and its uses

Explain artificial neural networks Describe how genetic algorithms are used Explain natural-language processing and its advantages and disadvantages Summarize the advantages of integrating AI technologies into decision support systems Explain contextual computing

What Is Artificial Intelligence? Artificial intelligence (AI) Consists of related technologies that try to simulate and reproduce human thought and behavior Includes thinking, speaking, feeling, and reasoning AI technologies Involve computer application to areas that require knowledge, perception, reasoning, understanding, and cognitive abilities Concerned with generating and displaying knowledge and facts

AI Technologies Supporting Decision Making Decision makers use information technologies in decision-making analyses of: What-is – Analysis used in transaction- processing systems and management information systems What-if – Analysis used in decision support systems

13.1 Applications of AI Technologies

Involve application of AI Excel at performing simple, repetitive tasks Robots Involve application of AI Excel at performing simple, repetitive tasks Free workers from tedious or hazardous jobs Have limited mobility Operation is controlled by a computer program that includes commands Includes programming languages for controlling Variable Assembly Language (VAL)

Use following programming languages Robots Use following programming languages Variable Assembly Language (VAL) Functional Robotics (FROB) A Manufacturing Language (AML) Honda’s Advanced Step in Innovative Mobility (ASIMO) Most advanced and most popular robots Coordinates with other robots Personal robots: Posses limited mobility, vision, and speech capabilities

Advantages of robots over humans in the workplace Robotics Advantages of robots over humans in the workplace Never fall in love with coworkers, get insulted, or call in sick Are consistent Used in environments that are hazardous to humans Risk of spying for competitors, asking for a raise, or lobbying for longer breaks does not exist

Expert Systems Mimics human expertise in a field to solve a problem in a well-defined area Used for activities that human experts have already handled successfully Tasks in medicine, geology, education, and oil exploration Work with heuristic data which encourages applying knowledge based on experience to solve or describe a problem

Components of an Expert System Knowledge acquisition facility Software package Has manual or automated methods for acquiring and incorporating new rules and facts so the expert system is capable of growth Knowledge base Similar to a database, but in addition to storing facts and figures it keeps track of rules and explanations associated with facts Includes factual, heuristic, meta types of knowledge

Components of an Expert System Knowledge base management system (KBMS) Similar to a DBMS Used to keep the knowledge base updated, with changes to facts, figures, and rules User interface: Provides user-friendly access to the expert system

Components of an Expert System Explanation facility Performs tasks similar to what a human expert does by explaining to end users how recommendations are derived Inference engine Similar to the model base component of a decision support system Uses techniques of forward and backward chaining to manipulate a series of rules

Components of an Expert System Forward chaining: Series of “if-then-else” condition pairs is performed Backward chaining: Expert system starts with the goal and backtracks to find the right solution

13.1 An Expert System Configuration

Uses of Expert Systems Airline industry Forensics lab work Banking and finance Education Food industry Personnel management Security US Government Agriculture

Criteria for Using Expert Systems Experience and knowledge of several experts is available Knowledge can be represented as rules or heuristics Decision or task has already been handled successfully by human experts Decision or task requires consistency and standardization

Criteria for Using Expert Systems Subject domain is limited Decision or task involves many rules and complex logic Involves scarcity of experts in the organization

Criteria for Not Using Expert Systems Very few rules are involved Existence of too many rules that slow down the processing capability to unacceptable levels Well-structured numerical problems involved Broad range of topics is involved, but there are not many rules Disagreement among experts

Advantages of Expert Systems Never become distracted, forgetful, or tired Duplicate and preserve the expertise of scarce experts Preserve the expertise of retiring or relieving employees Create consistency in decision making Improve the decision-making skills of nonexperts

Offers a solution after searching for a match Case-Based Reasoning Problem-solving technique that matches a new case with a previously solved case and its solution, stored in a database Offers a solution after searching for a match Failing to find a match, human expert is required to solve the problem

Software capable of reasoning and following rule-based processes Intelligent Agents Software capable of reasoning and following rule-based processes Popular in e-commerce Known as: Bots (short for robots) Virtual agents (VAs) Intelligent virtual agents (IVAs)

Characteristics of Intelligent Agents Adaptability Autonomy Collaborative behavior Humanlike interface Mobility Reactivity

Applications of Intelligent Agents Web marketing: Collecting following information about customers Items purchased Demographic information Expressed and implied preferences Virtual catalogs Display product descriptions based on customers’ previous experiences and preferences

Categories of Available Intelligent Agents Shopping and information Personal Data-mining Monitoring and surveillance

Shopping and Information Agents Help users navigate through the vast resources available on the Web Provide better results in finding information Serve as: Search engines Site reminders Personal surfing assistants

Perform specific tasks for a user Personal Agents Perform specific tasks for a user Remembering information for filling out Web forms Completing e-mail addresses after the first few characters are typed Tasks performed by e-mail personal agent Generate auto-response messages Forward incoming messages Create e-mail replies based on the content of incoming messages

Work with a data warehouse Data-Mining Agents Work with a data warehouse Detect trends and discover information and relationships among data items that were not readily apparent Helps detect potential problems that may arise in future which enables to come up with a solution that minimizes the negative effects of the problem

Monitoring and Surveillance Agents Track and report on computer equipment and network systems to predict when a system crash or failure might occur

Fuzzy Logic Allows a smooth, gradual transition between human and computer vocabularies Deals with variations in linguistic terms by using a degree of membership Designed to help computers simulate vagueness and uncertainty in common situations Works based on the degree of membership in a set

13.3 Degree of Membership in a Fuzzy System

Areas Where Fuzzy Logic is Used Search engines Chip design Database management systems Software development

Artificial Neural Networks (ANNs) Networks that learn and are capable of performing tasks that are difficult with conventional computers Playing chess, recognizing patterns in faces and objects, and filtering spam e-mail Used for poorly structured problems Use patterns instead of the if-then-else rules used by the expert systems Create a model based on input and output

13.4 Artificial Neural Network Configuration

Tasks Involving the Use of ANNs Bankruptcy prediction Credit rating Investment analysis Oil and gas exploration Target marketing

Genetic Algorithms (GAs) Search algorithms that mimic the process of natural evolution Used to generate solutions to optimization and search problems using mutation, selection, crossover, and chromosome techniques Designed to find the combination of inputs that generate the most desirable outputs

Natural Language Processing (NLP) Developed so that users can communicate with computers in human language Provides question-and-answer setting that’s natural and easier for people to use Useful with databases Use for: Call routing Stock and bond trading Banking by phone

13.2 NLP Systems

Categories in NLP Systems Interface to databases Machine translation Text scanning and intelligent indexing programs for summarizing large amounts of text Generating text for automated production of standard documents Speech systems for voice interaction with computers

Activities Performed by NLP Systems Interfacing Accepting human language as input Carrying out the corresponding command Generating the necessary output Knowledge acquisition Using the computer to read large amounts of text and understand the information Summarize important points and store information so the system can respond to inquiries about the content

Integrating AI Technologies into Decision Support Systems AI technologies help improve the quality of decision support systems (DSSs) Adds explanation capabilities by integrating expert systems and learning capabilities by integrating ANNs Creates an interface that is easier to use by integrating an NLP system Systems are called integrated DSSs (IDSSs)

Contextual Computing Computing environment that is always present and is capable perceive the surroundings and offer recommendations based on individual need and requirement Based on the principle that computers can both sense and react to the environments Similar to how human brains understand and interpret stimuli

Achieved by using the information technologies Contextual Computing Allows for tailoring a course of action to a user in a situation and environment based on what it knows about the user Achieved by using the information technologies Computer networks Software Hardware Database systems AI technologies

Artificial intelligence (AI) Artificial neural networks (ANNs) Backward chaining Case-based reasoning (CBR) Contextual computing Data-mining agents Expert systems Explanation facility

Forward chaining Fuzzy logic Genetic algorithms (GAs) Inference engine Intelligent agents Knowledge acquisition facility Knowledge base Knowledge base management system (KBMS)

Monitoring and surveillance agents Natural-language processing (NLP) Personal agents Robots Shopping and information agents

Artificial intelligence technologies apply computers to areas that require knowledge, perception, reasoning, understanding, and cognitive abilities Intelligent agents are becoming more popular, especially in e-commerce Fuzzy logic is designed to help computers simulate vagueness and uncertainty in common situations

Genetic algorithms examine complex problems without any assumptions of what the correct solution should be Size and complexity of the human language has made developing NLP systems difficult Contextual computing allows for tailoring a course of action to a user in a situation and environment based on its knowledge about the user