• 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
Expert Systems
Expert Systems

...  Knowledge-based expert systems or simply expert systems  An expert system is software that attempts to reproduce the performance of one or more human experts, most commonly in a specific problem domain (Wikipedia)  Use human knowledge to solve problems that normally would require human intellige ...
Personified Systems - Eldacur Technologies
Personified Systems - Eldacur Technologies

The DARPA High Performance Knowledge Bases
The DARPA High Performance Knowledge Bases

... military engineering solutions to trafficobstruction problems, such as destroyed bridges and blocked tunnels. Good challenge problems must satisfy several, often conflicting, criteria. A challenge problem must be challenging: It must raise the bar for both technology and science. A problem that requ ...
1983 - Derivational Analogy and Its Role in Problem Solving
1983 - Derivational Analogy and Its Role in Problem Solving

... accrue from such an endeavor? Perhaps the best way to answer this question is by analysis of where the simple solution transformation process falls short and how such problems may be alleviated or circumvented by preserving more information from which qualitatively different analogies may be drawn. ...
2012 version HERE . - School of Computer Science
2012 version HERE . - School of Computer Science

... There’s no easy way: learn to build ever more complex models of natural information processing systems, try to understand the engineering design problems that evolution addressed; always ask questions about what information is needed, why it is needed, what information is available, how is it acquir ...
From: AAAI Technical Report S-0 -0 . Compilation copyright © 200
From: AAAI Technical Report S-0 -0 . Compilation copyright © 200

... Copyright © 2003, AAAI Press The American Association for Artificial Intelligence 445 Burgess Drive Menlo Park, California 94025 ISBN 1-57735-180-0 SS-03-03 AAAI retains the right of first refusal to any publication arising from this AAAI event, and retains compilation copyright. Please do not make ...
Introduction to Artificial Intelligence
Introduction to Artificial Intelligence

... gurus at Sentient Technologies Holdings Ltd. of San Francisco, the software for sentient computers, which they are already installing at key customer sites, goes beyond natural language recognition, unstructured searching, machine learning, and deep knowledge. ...
An Oz-Centric Review of Interactive Drama and
An Oz-Centric Review of Interactive Drama and

... For many people, the phrase believable agent conjures up some notion of an agent that tells the truth, or an agent you can trust. But this is not what is meant at all. Believable is a term coming from the character arts. A believable character is one who seems lifelike, whose actions make sense, who ...
Description of Attraction-Repulsion Forces by
Description of Attraction-Repulsion Forces by

Multi agent systems simulator in Common Lisp
Multi agent systems simulator in Common Lisp

... a theoretical background into artificial intelligence and, more specifically, into multi agent systems. In chapter 3, I will present the Common Lisp language and its main features, along with the LispWorks IDE I have chosen to use to develop cl-ass in. Chapter 4 is devoted to how cl-ass was created ...
Testing of Various Embedded System with Artificial Intelligence
Testing of Various Embedded System with Artificial Intelligence

... All Rights Reserved © 2015 IJARCET ...
The Dynamical Hypothesis in Cognitive Science: A review essay of
The Dynamical Hypothesis in Cognitive Science: A review essay of

... homeomorphic to Rn, and is the most common setting for much of geometric dynamical systems theory.” And the explanation of key concepts like flow, gradient system, orbit, Poincaré map, trajectory, and vector field are equally technical for non mathematicians. The point is that either one has a relat ...
short
short

download
download

11. Building Information Systems
11. Building Information Systems

... THE DIGITAL FIRM ...
Safe Artificial Intelligence and Formal Methods
Safe Artificial Intelligence and Formal Methods

The RacerPro Knowledge Representation and Reasoning System
The RacerPro Knowledge Representation and Reasoning System

... the SUMO ontology [64]. Explanation features for inconsistent concepts are available for knowledge bases as large as Snomed CT (the RacerPro explanation facility uses built-in data structures of the tableau reasoner). It should be noted that Abox reasoning services can be used for problem solving. F ...
The RacerPro Knowledge Representation and Reasoning System1
The RacerPro Knowledge Representation and Reasoning System1

... the SUMO ontology [64]. Explanation features for inconsistent concepts are available for knowledge bases as large as Snomed CT (the RacerPro explanation facility uses built-in data structures of the tableau reasoner). It should be noted that Abox reasoning services can be used for problem solving. F ...
Integrating Logical Reasoning into Everyday Applications AAAI Press
Integrating Logical Reasoning into Everyday Applications AAAI Press

... Menlo Park, California 94025 USA AAAI maintains compilation copyright for this technical report and retains the right of first refusal to any publication (including electronic distribution) arising from this AAAI event. Please do not make any inquiries or arrangements for hardcopy or electronic publ ...
Principles of Artificial Intelligence
Principles of Artificial Intelligence

... • What is the informational and algorithmic basis of interagent interaction, communication, and coordination? • Under what conditions can self-interested rational agents cooperate to achieve a common good? • How do groups and coalitions form? • How do different social organizations (democracies, eco ...
Mis – MASTER STUDENTS- Presentation 10
Mis – MASTER STUDENTS- Presentation 10

... • Expert systems • Model human knowledge as a set of rules that are collectively called the knowledge base • From 200 to 10,000 rules, depending on complexity • The system’s inference engine searches through the rules and “fires” those rules that are triggered by facts gathered and entered by the us ...
Turing`s Legacy
Turing`s Legacy

Artificial Intelligence and the `Good Society`
Artificial Intelligence and the `Good Society`

CS6659-ARTIFICIAL INTELLIGENCE
CS6659-ARTIFICIAL INTELLIGENCE

... In optimization problems, the aim is to find the best state according to an objective function the optimization problem is then: Find values of the variables that minimize or maximize the objective function while satisfying the constraints. 31. What is Hill-climbing search? The Hill-climbing algorit ...
Reports on the 2015 AAAI Workshop Series
Reports on the 2015 AAAI Workshop Series

... their crawling abilities. Finally, Tiaro Vaquero presented the implementation of a system dedicated to the planning and scheduling of activities of daily living, involving multiple users (especially elders) and human-robot interaction with multiple mobile assistive and collaborative robots. The thir ...
< 1 ... 16 17 18 19 20 21 22 23 24 ... 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