• Study Resource
  • Explore
    • Arts & Humanities
    • Business
    • Engineering & Technology
    • Foreign Language
    • History
    • Math
    • Science
    • Social Science

    Top subcategories

    • Advanced Math
    • Algebra
    • Basic Math
    • Calculus
    • Geometry
    • Linear Algebra
    • Pre-Algebra
    • Pre-Calculus
    • Statistics And Probability
    • Trigonometry
    • other →

    Top subcategories

    • Astronomy
    • Astrophysics
    • Biology
    • Chemistry
    • Earth Science
    • Environmental Science
    • Health Science
    • Physics
    • other →

    Top subcategories

    • Anthropology
    • Law
    • Political Science
    • Psychology
    • Sociology
    • other →

    Top subcategories

    • Accounting
    • Economics
    • Finance
    • Management
    • other →

    Top subcategories

    • Aerospace Engineering
    • Bioengineering
    • Chemical Engineering
    • Civil Engineering
    • Computer Science
    • Electrical Engineering
    • Industrial Engineering
    • Mechanical Engineering
    • Web Design
    • other →

    Top subcategories

    • Architecture
    • Communications
    • English
    • Gender Studies
    • Music
    • Performing Arts
    • Philosophy
    • Religious Studies
    • Writing
    • other →

    Top subcategories

    • Ancient History
    • European History
    • US History
    • World History
    • other →

    Top subcategories

    • Croatian
    • Czech
    • Finnish
    • Greek
    • Hindi
    • Japanese
    • Korean
    • Persian
    • Swedish
    • Turkish
    • other →
 
Profile Documents Logout
Upload
Representing Probabilistic Rules with Networks of
Representing Probabilistic Rules with Networks of

... may learn faster (i.e., converge in fewer learning steps to an acceptable solution) than a network learning from scratch (Shavlik & Towell, 1989; Gallant, 1988). A second reason is that in many domains it is difficult to get a significant number of training examples. In this case we clearly want to ...
Chapter 02 for Neuro-Fuzzy and Soft Computing
Chapter 02 for Neuro-Fuzzy and Soft Computing

... - SC is an innovative approach to constructing computationally intelligent systems ...
MAI0203 Lecture 7: Inference and Predicate Calculus
MAI0203 Lecture 7: Inference and Predicate Calculus

... Mapping of formula to truth values: To assign a truth value, first, the arguments of a predicate symbol are interpreted, afterwards it is determined whether the corresponding relation holds in the structure. If all atomic formula are associated with truth values, more complex formulas can be interpr ...
Multi-Agent Case-Based Diagnosis in the Aircraft Domain
Multi-Agent Case-Based Diagnosis in the Aircraft Domain

... weather conditions, temperature, etc.), and logbook entries can be received, too. The PFR data and the additional data have to be correlated to assign the additional data to the corresponding PFR item. This task is done by the correlation agent. The extended PFR items are sent to the coordination ag ...
Chapter 11 - Barbara Hecker
Chapter 11 - Barbara Hecker

... • Identification of underlying patterns, categories, and behaviors in large data sets, using techniques such as neural networks and data mining Artificial Intelligence (AI) technology: • Computer-based systems based on human behavior, with the ability to learn languages, accomplish physical tasks, u ...
Artificial Intelligence techniques: An introduction to their use for
Artificial Intelligence techniques: An introduction to their use for

... problem, a pattern matcher and a rule applier. The pattern matcher refers to the working memory to decide which rules are relevant, then the rule applier chooses what rule to apply. New information created by the action (then-) part of the rule applied is added to the working memory and the match-se ...
Artificial Intelligence I: introduction
Artificial Intelligence I: introduction

... In a dynamically scoped language an identifier can be referred to, not only in the block where it is declared, but also in any function or procedure called from within that block, even if the called procedure is declared outside the block ...
CS325 Artificial Intelligence Chs. 9, 12 – Knowledge Representation
CS325 Artificial Intelligence Chs. 9, 12 – Knowledge Representation

... military. This Lisp application alone is said to have paid back for all US investments in AI research at that time. SPIKE, the planning and scheduling application for the Hubble Space Telescope. Also used by several other large telescopes. CYC, one of the largest software systems written. Representa ...
Dan Leach Resume
Dan Leach Resume

... Instrumented the F6X and F2K DLLs in such a way that communications sessions may be captured (by activating a back door). These can be used both for static diagnostic purposes and as input to the applications that generated them. Replay allows debugging of the UI without the need for a physical inst ...
Understanding Computers, 11/e, Chapter 12
Understanding Computers, 11/e, Chapter 12

... would be expected from a human expert  Knowledge base: database containing facts provided by human experts and rules the system should use to make decisions based on those facts  Inference engine: program that applies the rules to the data stored in the knowledge base, in order to reach decisions ...
Intelligent Environmental Decision Support Systems - Model
Intelligent Environmental Decision Support Systems - Model

... sensitive our decision is to snu11 variations in the given \veight and value of the relevant variables. The role of sociocultural and econOInic issues lin1it5 the use of standard database'i. Confidence cannot be increased in the results when facing silniIar situations, because these IEDSS arc vcry s ...
Artificial Intelligence and Environmental Decision Support Systems
Artificial Intelligence and Environmental Decision Support Systems

... problem specific EDSS and situation and problem specific EDSS. Problem specific EDSS are tailored to relatively narrow environmental problems (or domains), but they are applicable to a wide range of different locations (or situations) in the best tradition of KBS. Situation and problem specific EDSS ...
Fuzzy Systems and Neuro-Computing in Credit Approval
Fuzzy Systems and Neuro-Computing in Credit Approval

... steps. The system processes imprecise information; therefore, for a given set of input variables it works through all the rules. So Happy Together Fuzzy logic and neural networks are complementary technologies in the design of intelligent systems. Each method has its pros and cons. For example: • Ar ...
The Next Knowledge Medium
The Next Knowledge Medium

... civilization dramatically. The article is in three parts: stories, models, and predictions. The stories describe processes of cultural change that have been studied by historians and anthropologists. They provide a historical context for considering present and future cultural changes. To illuminate ...
Vasant Dhar
Vasant Dhar

... Principal Investigator, A Knowledge-Based Approach for Assessing Inherent Risk, two year grant funded by the Peat Marwick International Research Foundation, June 1985 -- June 1987. Principal Investigator, Knowledge-Based Support for Back-Office Processing in Banking (automation of large volumes of f ...
Enhancing the Scientific Process with Artificial
Enhancing the Scientific Process with Artificial

... Knowledge evaluation. Knowledge must be carefully evaluated, not only for empirical corroboCognitive Aspects ration, but also for conceptual and logical consistency with existing knowledge. First, the concepts in of Artificial Intelligence hypotheses that are candidates for inclusion into a theory m ...
X - Natural Language Processing Lab., Korea University
X - Natural Language Processing Lab., Korea University

... missing, or poorly defined information. 3. Answers that are neither exact nor optimal, but are in some sense “sufficient”. ...
Employing a Java Expert System Shell for Intelligent - CEUR
Employing a Java Expert System Shell for Intelligent - CEUR

... usually a qualitative or sometimes a deep procedural understanding of a concept. The development of such exploratory environments or activities is quite time consuming. In addition, the extent to which they achieve the expected learning objectives relies on the effectiveness of the students’ explora ...
What kind of cognitive process is argumentation?
What kind of cognitive process is argumentation?

... Minimally argumentative agents – not for passing Turing tests but for human/machine interaction and knowledge acquisition This is an exercise in android epistemology... ...
limitations and performance of mrpii/erp systems - ICPR
limitations and performance of mrpii/erp systems - ICPR

... of queue, set-up and run times on the shopfloor. Net requirement patterns generated do not consider the availability of resource simultaneously, but identify resources required as a separate, subsequent activity. MRPII/ERP systems may be loaded with a predetermined scrap rate. Any increase in this r ...
Document
Document

... • Knowing the potential impact of information systems and having the ability to put this knowledge to work can result in a successful personal career, organizations that reach their goals, and a society with a higher quality of life. – Identify the basic types of business information systems and dis ...
Approaches to Artificial Intelligence
Approaches to Artificial Intelligence

... of this behaviour in other animals; for others, its biological underpinnings in the central nervous systemj still others, its societal dependencies. Those of us in knowledge representation and reasoning focus on what. Zenon Pylyshyn has called the "cognitive penet.rabilit.y" of int.elligent. behavio ...
introduction
introduction

... • plan sequences of actions to complete a goal • offer advice based on rules and situations • may not necessarily imitate human senses and thought processes ...
Lecture IV--LogicAgentandFirstOrderLogic
Lecture IV--LogicAgentandFirstOrderLogic

... and complete inference procedure i.e., the procedure will answer any question whose answer follows from what is known about KB ...
research statement
research statement

... associative learning. I specialize in the field of classification, construction of wellgeneralizing classifiers, construction of associative self-optimizing neural networks, associative neural graphs and artificial associative systems. My future research aims to develop new models of neurons, algori ...
< 1 ... 5 6 7 8 9 10 11 12 13 ... 32 >

Expert system



In artificial intelligence, an expert system is a computer system that emulates the decision-making ability of a human expert.Expert systems are designed to solve complex problems by reasoning about knowledge, represented primarily as if–then rules rather than through conventional procedural code. The first expert systems were created in the 1970s and then proliferated in the 1980s. Expert systems were among the first truly successful forms of AI software.An expert system is divided into two sub-systems: the inference engine and the knowledge base. The knowledge base represents facts and rules. The inference engine applies the rules to the known facts to deduce new facts. Inference engines can also include explanation and debugging capabilities.
  • studyres.com © 2025
  • DMCA
  • Privacy
  • Terms
  • Report