Info Systems : Chapter 13

Artificial intelligence (AI) consists of related technologies that try to simulate and reproduce human thought behavior, including thinking, speaking, feeling, and reasoning. Artificial intelligence (AI) technologies apply computers to areas that require knowledge, perception, reasoning, understanding, and cognitive abilities. Artificial neural networks (ANNs) are networks that learn and are capable of performing tasks that are difficult with conventional computers, such as playing chess, recognizing patterns in faces and objects, and filtering spam e-mail. Data-mining agents work with a data warehouse, detecting trends and discovering new information and relationships among data items that were not readily apparent. Expert systems mimic human expertise in a particular field to solve a problem in a well-defined area. Fuzzy logic allows a smooth, gradual transition between human and computer vocabularies and deals with variations in linguistic terms by using a degree of membership. Intelligent agents are software capable of reasoning and following rule-based processes; they are becoming more popular, especially in e-commerce. A knowledge base management system (KBMS), similar to a DBMS, is used to keep the knowledge base updated, with changes to facts, figures, and rules. Machine Learning is a process and procedure by which knowledge is gained through experience. In other words, computers learn without being explicitly programmed. Monitoring and surveillance agents usually track and report on computer equipment and network systems to predict when a system crash or failure might occur. Personal agents perform specific tasks for a user, such as remembering information for filling out Web forms or completing e-mail addresses after the first few characters are typed. Robots are one of the most successful applications of AI. They perform well at simple, repetitive tasks and can be used to free workers from tedious or hazardous jobs. Shopping and information agents help users navigate through the vast resources available on the Web and provide better results in finding information. These agents can navigate the Web much faster than humans and gather more consistent, detailed information. They can serve as search engines, site reminders, or personal surfing assistants. in backward chaining, the expert system starts with the goal—the “then” part—and backtracks to find the right solution. case-based reasoning (CBR) is a problem-solving technique that matches a new case (problem) with a previously solved case and its solution, both stored in a database. After searching for a match, the CBR system offers a solution; if no match is found, even after supplying more information, the human expert must solve the problem. contextual computing refers to a computing environment that is always present, can feel our surroundings, and—based on who we are, where we are, and whom we are with—offer recommendations. An explanation facility performs tasks similar to what a human expert does by explaining to end users how recommendations are derived. In forward chaining, a series of “if-then-else” condition pairs is performed. genetic algorithms (GAs) are search algorithms that mimic the process of natural evolution. They are used to generate solutions to optimization and search problems using such techniques as mutation, selection, crossover, and chromosome. An inference engine is similar to the model base component of a decision support system. By using different techniques, such as forward and backward chaining, it manipulates a series of rules. A knowledge acquisition facility is a software package with manual or automated methods for acquiring and incorporating new rules and facts so the expert system is capable of growth. A knowledge base is similar to a database, but in addition to storing facts and figures it keeps track of rules and explanations associated with facts. natural-language processing (NLP) was developed so users could communicate with computers in human language. NLP systems usually perform two types of activities. The first is interfacing: accepting human language as input, carrying out the corresponding command, generating the necessary output. The second is knowledge acquisition: using the computer to read large amounts of text and understanding information well enough to summarize important points and store information so the system can respond to inquiries about the context. Soft Robotics is the specific subfield of robotics dealing with constructing robots from highly compliant materials such as elastomer.