• 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
Get Smart: How Intelligent Technology will Enhance
Get Smart: How Intelligent Technology will Enhance

... systems will become our skilled assistants, adapting to us as needed and – over time – disappearing into everyday life. This change will not come over night, as the unfulfilled dream of smart reminds us. However, continuing innovation and technology advances will help today’s smart systems overcome ...
1 HYBRID EXPERT SYSTEM OF ROUGH SET AND NEURAL
1 HYBRID EXPERT SYSTEM OF ROUGH SET AND NEURAL

... There are several reasons for developing expert system models that have neural network as their knowledge bases. By using the learning algorithms from previous parts, expert system can be generated from training examples. This would be especially helpful where there is a large amount of noisy data. ...
Intelligent Environmental Decision Support Systems - Model
Intelligent Environmental Decision Support Systems - Model

... The increasing rhythm of industrialisation, urbanisation and population growth negatively affects environmental quality and hence plant, animal and hUllUll life. Whenever we attclllpt to tackle these cllviromnental issues and to analyse the resulting tradeoffs between econo111ic, ecological, social ...
Chapter 4 Diagnostic Expert Systems: From Expert`s Knowledge to
Chapter 4 Diagnostic Expert Systems: From Expert`s Knowledge to

... Expert systems found broad application in fault diagnosis from their early stages because an expert system simulates human reasoning about a problem domain, performs reasoning over representations of human knowledge and solves problems using heuristic knowledge rather than precisely formulated relat ...
randomizing the knowledge acquisition bottleneck
randomizing the knowledge acquisition bottleneck

... compiler and was later formalized into what is now termed an expert compiler. Expert compilers use rules (i.e., expert systems) to translate fourth generation languages and beyond. Fourth generation languages represent the best success story to date in the broad field of software engineering [4]. As ...
Vita 9/27/91 - University of Southern California
Vita 9/27/91 - University of Southern California

... pp. 240-252. (12th Most Cited IJAIS Paper 2008-2013) (14th most downloaded paper from IJAIS for October –December 2008. 19th most downloaded paper from IJAIS for January – March 2009, 23rd most downloaded paper for July – September 2009). http://dx.doi.org/10.1016/j.accinf.2008.09.001 12th Most Cite ...
Contemporary Cybernetics and Its Facets of Cognitive Informatics
Contemporary Cybernetics and Its Facets of Cognitive Informatics

... nets [26], and Widrow and Lehr initiated the technology of artificial neural networks in the 1950s [59] based on multilevel, distributed, dynamic, interactive, and self-organizing nonlinear networks [1], [8], [12]. The concepts of robotics [6] and expert systems [11] were developed in the 1970s and ...
turing test - Department of Intelligent Systems
turing test - Department of Intelligent Systems

... Inelligent systems, 7.10.2015 ...
Practical Artificial Intelligence For Dummies
Practical Artificial Intelligence For Dummies

... Today, we are confronted with an emerging suite of intelligent systems that do things in a way that we do not quite understand. What is actually frightening is that we might not know enough about these systems to be able to evaluate them appropriately. So every time a co‐worker talks about deep lear ...
What is Artificial Intelligence? • Meet ELIZA • Written between 1964-1966
What is Artificial Intelligence? • Meet ELIZA • Written between 1964-1966

... • Processes Human Text • Does what a physiologist does • What is Artificial Intelligence? ...
Unit2 - คณะเทคโนโลยีสารสนเทศและการสื่อสาร มหาวิทยาลัยพะเยา
Unit2 - คณะเทคโนโลยีสารสนเทศและการสื่อสาร มหาวิทยาลัยพะเยา

... Reachable goal: a state for which there exists a sequence of operators to reach it. State space: set of all reachable states from initial state (possibly infinite). Cost function: a function that assigns a cost to each operation. Performance: – cost of the final operator sequence – cost of finding t ...
validation and verification of knowledge bases in the context of
validation and verification of knowledge bases in the context of

Survey on Heuristic Search Techniques to Solve Artificial
Survey on Heuristic Search Techniques to Solve Artificial

... complicated; these problems cannot be solved using direct techniques that are available [12]. We need to solve these problems using suitable search method equipped with direct techniques whichever is available to guide the search. Heuristic is a search technique where the efficiency of search is imp ...
ShimonWhiteson - Homepages of UvA/FNWI staff
ShimonWhiteson - Homepages of UvA/FNWI staff

... ShimonWhiteson Research Interests My research is focused on artificial intelligence. I believe that intelligent agents are essential to improving our ability to solve complex, real-world problems. Consequently, my research focuses on the key algorithmic challenges that arise in developing control sy ...
Knowledge Based System and Database Management System: An
Knowledge Based System and Database Management System: An

... IS applications. The reasons for these are slowly emerging. Most expert systems require rules (or a knowledge base) and facts (or a database) to be integrated to make an application useful in real-world. Success in the use of expert systems is hinged on effectively linking the KBS with the firm’s DB ...
Toward AI for Human Beings: Human Centric AI Zinrai
Toward AI for Human Beings: Human Centric AI Zinrai

... Ltd.”, “Fujitsu Limited”). By leveraging cognitive technology, it will be possible to load specific data of the Financial Supervisory Agency, financial documents of banks, as well as open data from sources such as social media sites and Wikipedia, and use this as a database allowing analysis from va ...
Management Information Systems Chapter 12 Enhancing Decision
Management Information Systems Chapter 12 Enhancing Decision

... Management Information Systems Chapter 12 Enhancing Decision Making Decision Making and Information Systems ...
On Agents and Grids: Creating the Fabric for a New Generation of
On Agents and Grids: Creating the Fabric for a New Generation of

323-670 ปัญญาประดิษฐ์ (Artificial Intelligence)
323-670 ปัญญาประดิษฐ์ (Artificial Intelligence)

... techniques that allow computers to "learn". • At a general level, there are two types of learning: inductive, and deductive. Inductive machine learning methods extract rules and patterns out of massive ...
Lecture 15 - Wiki Index
Lecture 15 - Wiki Index

... Recent work studies the formation of granules with different criteria from a rough computing point of view (Skowron & Stepaniuk, 2007). When searching for optimal solutions satisfying some constraints, one of the challenges is that these constraints are often vague and imprecise. In addition, specif ...
Integrating AI Techniques in Requirements Phase: A Literature Review
Integrating AI Techniques in Requirements Phase: A Literature Review

... Based on these aforementioned research directions, various sub areas have been identified; a pictorial representation of the same is given as follows (in Fig 1): ...
Topic_2B_Expert_Systems
Topic_2B_Expert_Systems

...  Completed in 1991, SPOTLIGHT proved highly popular with sales reps and their clients  Demonstrated feasibility of expert systems based on conventional technology - written in C for a PC platform, rather than in an AI language such as LISP for AI workstation ...
Progress in Business Intelligence System research: A literature
Progress in Business Intelligence System research: A literature

... 5 % papers discuss about integrated between BI and Data Mining. A data mining methodology called Business Intelligencedriven Data Mining (BIdDM) combines knowledge-driven data mining and method-driven data mining, and fills the gap between business intelligence knowledge and existent various data mi ...
Introduction to AI
Introduction to AI

... You have a search tree with a branching factor of b and a maximum depth of m. The depth of the shallowest goal node is d. You are considering searching the tree using either a depth-first search agent or a breathfirst search agent. Which one will have the best space complexity? Explain. ...
Human Skill - Alex Quinn
Human Skill - Alex Quinn

< 1 ... 18 19 20 21 22 23 24 25 26 ... 143 >

AI winter

In the history of artificial intelligence, an AI winter is a period of reduced funding and interest in artificial intelligence research. The term was coined by analogy to the idea of a nuclear winter. The field has experienced several hype cycles, followed by disappointment and criticism, followed by funding cuts, followed by renewed interest years or decades later. There were two major winters in 1974–80 and 1987–93 and several smaller episodes, including: 1966: the failure of machine translation, 1970: the abandonment of connectionism, 1971–75: DARPA's frustration with the Speech Understanding Research program at Carnegie Mellon University, 1973: the large decrease in AI research in the United Kingdom in response to the Lighthill report, 1973–74: DARPA's cutbacks to academic AI research in general, 1987: the collapse of the Lisp machine market, 1988: the cancellation of new spending on AI by the Strategic Computing Initiative, 1993: expert systems slowly reaching the bottom, and 1990s: the quiet disappearance of the fifth-generation computer project's original goals.The term first appeared in 1984 as the topic of a public debate at the annual meeting of AAAI (then called the ""American Association of Artificial Intelligence""). It is a chain reaction that begins with pessimism in the AI community, followed by pessimism in the press, followed by a severe cutback in funding, followed by the end of serious research. At the meeting, Roger Schank and Marvin Minsky—two leading AI researchers who had survived the ""winter"" of the 1970s—warned the business community that enthusiasm for AI had spiraled out of control in the '80s and that disappointment would certainly follow. Three years later, the billion-dollar AI industry began to collapse.Hypes are common in many emerging technologies, such as the railway mania or the dot-com bubble. An AI winter is primarily a collapse in the perception of AI by government bureaucrats and venture capitalists. Despite the rise and fall of AI's reputation, it has continued to develop new and successful technologies. AI researcher Rodney Brooks would complain in 2002 that ""there's this stupid myth out there that AI has failed, but AI is around you every second of the day."" In 2005, Ray Kurzweil agreed: ""Many observers still think that the AI winter was the end of the story and that nothing since has come of the AI field. Yet today many thousands of AI applications are deeply embedded in the infrastructure of every industry."" He added: ""the AI winter is long since over.""
  • studyres.com © 2025
  • DMCA
  • Privacy
  • Terms
  • Report