User Interface: Provides the means for dialog between the user and system.
Explanation facility: Provides the user with Explanations of how a conclusion was reached or why a piece of knowledge is needed. They also need to be convinced that the solution isappropriate and applicable in their circumstances.
Inference Engine
accepts user input quarries and response to questions through the user interface and uses this dynamic information together with the static knowledge (the rules andfacts) stored in the knowledge base.
The inference process is carried out recursively in three stages (I) match (II) select (III) execute.During the match stage, the contents of working memory are compared to facts and rulescontained in the knowledge base.
Knowledge base contains facts and rules about some specialized knowledge domain.
Learning module implies that an organize or machine must be able to adapt to new situations.The job of Knowledge engineer is to extract the knowledge from the expert and other sourceslike book, journals, article etc.
Adaptive Interface A computer interface that automatically and dynamically adapts to the needs and competence of each individual user of the software.
Agents Agents are software programs that are capable of autonomous, flexible, purposeful and reasoning action in pursuit of one or more goals. They are designed to take timely action in response to external stimuli from their environment on behalf of a human. When multiple agents are being used together in a system, individual agents are expected to interact together as appropriate to achieve the goals of the overall system. Also called autonomous agents, assistants, brokers, bots, droids, intelligent agents, software agents.
AI Languages and Tools: AI software has different requirements from other, conventional software. Therefore, specific languages for AI software have been
developed. These include LISP, Prolog, and Smalltalk. While these languages often reduce the time to develop an artificial intelligence application, they can lengthen the time to execute the application. Therefore, much AI software is now written in languages such as C++ and Java, which typically increases development time, but shortens execution time. Also, to reduce the cost of AI software, a range of commercial software development tools have also been developed. Stottler Henke has developed its own proprietary tools for some of the specialized applications it is experienced in creating.
Algorithm : An algorithm is a set of instructions that explain how to solve a problem. It is usually first stated in English and arithmetic, and from this, a programmer can translate it into executable code (that is, code to be run on a computer).
Applications of Artificial Intelligence :
The actual and potential applications are virtually endless. Reviewing Stottler Henke's work will give you some idea of the range. In general, AI applications are used to increase the productivity of knowledge workers by intelligently automating their tasks;
or to make technical products of all kinds easier to use for both workers and consumers by intelligent automation of different aspects of the functionality of complex products.
Associative Memories :
Associative memories work by recalling information in response to an information cue.
Associative memories can be autoassociative or heteroassociative. Autoassociative memories recall the same information that is used as a cue, which can be useful to complete a partial pattern. Heteroassociative memories are useful as a memory.
Human long-term memory is thought to be associative because of the way in which one thought retrieved from it leads to another. When we want to store a new item of information in our long term memory it typically takes us 8 seconds to store an item that can't be associated with a pre-stored item, but only one or two seconds, if there is an existed information structure with which to associate the new item.
Autonomous Agents
A piece of AI software that automatically performs a task on a human's behalf, or even on the behalf of another piece of AI software, so together they accomplish a useful task for a person somewhere. They are capable of independent action in dynamic, unpredictable environments. "Autonomous agent" is a trendy term that is sometimes
reserved for AI software used in conjunction with the Internet (for example, AI software that acts as your assistance in intelligently managing your e-mail).
Autonomous agents present the best hope from gaining additional utility from computing facilities. Over the past few years the term "agent" has been used very loosely. Our definition of a software agent is: "an intelligent software application with the authorization and capability to sense its environment and work in a goal directed manner." Generally, the term "agent" implies "intelligence", meaning the level of complexity of the tasks involved approaches that which would previously have required human intervention.
Backtracking A control method used to search backwards for solutions Clauses Either a Prolog fact or rule.
Cognitive Science : Cognitive Science, as a discipline, is concerned with learning how animals (and machines) acquire knowledge, represent that knowledge, and how they manipulate those representations..
Computer Vision :Making sense of what we see is usually easy for humans, but very hard for computers. Practical vision systems to date are limited to working in tightly controlled environments. Synonym: machine vision
Domain : An overworked word for AI people. "Domain" can mean a variety of things including a subject area, field of knowledge, an industry, a specific job, an area of activity, a sphere of influence, or a range of interest, e.g., chemistry, medical diagnosis, putting out fires, operating a nuclear power plant, planning a wedding, diagnosing faults in a car. Generally, a domain is a system in which a particular set of rules, facts, or assumptions operates. Humans can usually easily figure out what's meant from the context in which "domain" is used; computers could probably not figure out what a human means when he or she says "domain."
Domain Expert
The person who knows how to perform an activity within the domain, and whose knowledge is to be the subject of an expert system. This person's or persons' knowledge and method of work are observed, recorded, and entered into a knowledge base for use
by an expert system. The domain expert's knowledge may be supplemented by written knowledge contained in operating manuals, standards, specifications, computer programs, etc., that are used by the experts. Synonym: subject-matter expert (SME).
Extension Language A general-purpose programming language accessible to the users of the application created with that language. LISP dialects (including Scheme) are often suitable extension languages.
Expert System
An expert system encapsulates the specialist knowledge gained from a human expert (such as a bond trader or a loan underwriter) and applies that knowledge automatically to make decisions. For example, the knowledge of doctors about how to diagnose a disease can be encapsulated in software. The process of acquiring the knowledge from the experts and their documentation and successfully incorporating it in the software is called knowledge engineering, and requires considerable skill to perform successfully.
Applications include customer service and helpdesk support, computer or network troubleshooting, regulatory tracking, autocorrect features in word processors, document generation such as tax forms, and scheduling.
Game Theory
Game theory is a branch of mathematics that seeks to model decision making in conflict situations.
Heuristics
A term describing an exploratory method of attacking a problem in which the solution is obtained by successive evaluations of progress toward the final results.
Inference Engine
The part of an expert system responsible for drawing new conclusions from the current data and rules. The inference engine is a portion of the reusable part of an expert system (along with the user interface, a knowledge base editor, and an explanation system), that will work with different sets of case-specific data and knowledge bases.
Knowledge-based Representations
The form or structure of databases and knowledge bases for expert and other intelligent systems, so that the information and solutions provided by a system are both accurate and complete. Usually involves a logically-based language capable of both syntactic and semantic representation of time, events, actions, processes, and entities. Knowledge
representation languages include Lisp, Prolog, Smalltalk, OPS-5, and KL-ONE.
Structures include rules, scripts, frames, endorsements, and semantic networks.
Knowledge
knowledge--1. In artificial intelligence, symbolic information used by a domain expert to solve problems. 2. Facts and relationships used to solve problems.
Knowledge-based Systems
Usually a synonym for expert system, though some think of expert systems as knowledge-based systems that are designed to work on practical, real-world problems.
Knowledge Elicitation
Synonym: knowledge acquisition.
Knowledge Engineering Knowledge engineering is the process of collecting knowledge from human experts in a form suitable for designing and implementing an expert system. The person conducting knowledge engineering is called a knowledge engineer.
Knowledge Representation
Knowledge representation is one of the two basic techniques of artificial intelligence, the other is the capability to search for end points from a starting point. The way in which knowledge is represented has a powerful effect on the prospects for a computer or person to draw conclusions or make inferences from that knowledge. Consider the representation of numbers that we wish to add. Which is easier, adding 10 + 50 in Arabic numerals, or adding X plus L in Roman numerals? Consider also the use of algebraic symbols in solving problems for unknown numerical quantities, compared with trying to do the same problems just with words and numbers.
LISP
LISP (short for list processing language), a computer language, was invented by John McCarthy, one of the pioneers of artificial intelligence. The language is ideal for representing knowledge (e.g., If a fire alarm is ringing, then there is a fire) from which inferences are to be drawn.
Machine Learning:
Machine learning refers to the ability of computers to automatically acquire new knowledge, learning from, for example, past cases or experience, from the computer's own experiences, or from exploration.
machine code--An operation code that a machine is designed to recognize.
Natural Language Processing
The study of strategies for computer programs to recognize and understand language in spoken and written form.
Neural Networks Neural networks are an approach to machine learning which developed out of attempts to model the processing that occurs within the neurons of the brain.
Procedural Language The traditional programming that is based on algorithms or a logical step-by-step process for solving a problem.
Proposition An expression about an object which can have either a true or false value.
Propositional Calculus The formal logic system used to define the true or false values of objects.
Pattern Recognition
1.The recognition of forms, shapes, or configurations by automatic means. A subfield of artificial intelligence. 2. The use of a computer to identify patterns.. 3. The use of statistical techniques and templates to process and classify patterns of data Plan Recognition
The goal of plan recognition is to interpret an agent's intentions by ascribing goals and plans to it based on partial observation of its behavior up to the current time. Divining the agent's underlying plan can be useful for many purposes including: interpreting the agent's past behavior, predicting the agent's future behavior, or acting to collaborate with (or thwart) the agent.
Robotics is the branch of technology that deals with the design, construction, operation, structural disposition, manufacture and application of robots.
Rule A clause that defines the relationship or relationships between facts and objects.
Relevance Feedback
Relevance feedback methods are used in information retrieval systems to improve the results produced from a particular query by modifying the query based on the user's reaction to the initial retrieved documents. Specifically, the user's judgments of the relevance or non-relevance of some of the documents retrieved are used to add new terms to the query and to reweight query terms. For example, if all the documents that the user judges as relevant contain a particular term, then that term may be a good one to add to the original query.
Rule-based System
An expert system based on IF-THEN rules for representing knowledge.
Scheme Langauge A LISP dialect often used within computer science curricula and programming language research.
Speech Recognition The ability of a computer to understand spoken words for the purpose of receiving commands and data input from the speaker.
Source Code
Symbolic coding in its original form before being processed by a computer.
Simulation
A simulation is a system that is constructed to work, in some ways, analogously to another system of interest. The constructed system is usually made simpler than the original system so that only the aspects of interest are mirrored. Simulations are commonly used to learn more about the behavior of the original system, when the original system is not available for manipulation. It may not be available because of cost or safety reasons, or it may not be built yet and the purpose of learning about it is to design it better. If the purpose of learning is to train novices, then cost, safety, or convenience are likely to be the reasons to work on a simulated system. The simulation may be a computer simulation (perhaps a realistic one of a nuclear power station's control room, or a mathematical one such as a spreadsheet for "what-if" analysis of a company's business); or it may be a small-scale physical model (such as a small-scale bridge, or a pilot chemical plant).
Turing Test--A game to determine whether a computer might be considered to possess intelligence, developed by British mathematician Alan Turing. Participants include two
respondents (a computer and a human) and a human examiner who tries to determine which of the unseen respondents is the human. According to this test, intelligence and the ability to think would be demonstrated by the computer's success in fooling the examiner.
Unification The pattern matching technique used by Prolog to match goals and sub-goals in a program.
Abbreviations
AI : Artificial Intelligence QA: Question Answering IR: Information Retrieval IE: Information Extraction
NLP: Natural Language Processing XML: Extensible Markup Language
AIML: Artificial Intelligence Markup Language ALICE: Artificial Linguistic Internet Computer Entity PNAMBIC: Pay No Attention to that Man Behind the Curtain
Bibliography
1. Charniak, E.: Introcuction of Artificial Intelligence, Narosa Publishing House.
2. Winton. P.H. : LISP, Narosa Publishing House.
3. Marcellus: Expert System Programming in TURBO PROLOG Prentice-Hall Inc. 1989.
4. Clark, K. L. & McCabe, F.G.: Micro-Prolog Prentice-Hall Inc. 1987
5. Elaine rich & Kevin Knight: Artificial Intelligence and Expert System, PHI.