Module 13 - Artificial Intelligence and Automation
Case-based reasoning (CBR)
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.
Machine learning
a process and procedure by which knowledge is gained through experience. In other words, computers learn without being explicitly programmed.
Forward chaining
a series of "if-then-else" condition pairs is performed
Knowledge acquisition facility
a software package with manual or automated methods for acquiring and incorporating new rules and facts so the expert system is capable of growth
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
Augmented intelligence
complements a decision maker capabilities, not replaces him or her.
Artificial intelligence (AI)
consists of related technologies that try to simulate and reproduce human thought behavior, including thinking, speaking, feeling, and reasoning. AI technologies apply computers to areas that require knowledge, perception, reasoning, understanding, and cognitive abilities.
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.
Soft robot
is made of elastomer, is simpler to make and less expensive and is used for an increasing number of applications.
Knowledge base
is similar storing facts and figures it keeps track of rules and explanations associated with facts.
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
Expert systems
mimic human expertise in a particular field to solve a problem in a well-defined area
Artificial neural networks (ANNs)
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
Robots
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
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.
Explanation facility
performs tasks similar to what a human expert does by explaining to end users how recommendations are derived
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.
Genetic algorithms (GAs)
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.
Knowledge base management system (KBMS)
similar to a DBMS, is used to keep the knowledge base updated, with changes to facts, figures, and rules
Intelligent agents
software capable of reasoning and following rule-based processes; they are becoming more popular, especially in e-commerce
Backward chaining
the expert system starts with the goal—the "then" part—and backtracks to find the right solution.
Monitoring and surveillance agents
usually track and report on computer equipment and network systems to predict when a system crash or failure might occur
Natural-language processing (NLP)
was developed so users could communicate with computers in human language
Data-mining agents
work with a data warehouse, detecting trends and discovering new information and relationships among data items that were not readily apparent