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Intelligent support systems
Intelligent support systems

... neural systems, that attempts to simulate massively parallel processing of interconnected elements in a network architecture. Neural computing:. The application of artificial neural network technology. Pattern recognition:. The ability of a neural network to establish patterns and characteristics in ...
2006 AAAI Spring Symposium Series
2006 AAAI Spring Symposium Series

... Therefore, the semantic web requires a large, dynamic, heterogeneous and shared information space to be effectively evaluated. On the other hand, the domain of e-government is unique because of its enormous challenge to achieve interoperability, given the manifold semantic differences of interpretat ...
Author template for journal articles
Author template for journal articles

KCL/SLaM Sponsorship Guidance
KCL/SLaM Sponsorship Guidance

CURRICULUM VITAE Academic Education Academic Employment
CURRICULUM VITAE Academic Education Academic Employment

... 12. Sivan Albagli, Rachel Ben-Eliyahu and Eyal Shimony, “Markov Networks based Ontology Matching, presented at NGITS 2009 - The 7th conference on Next Generation Information Technologies and Systems, 2009. 13. Fabrizio Angiulli, Rachel Ben-Eliyahu-Zohary and Luigi Palopoli. Tractable Strong Outlier ...
Review of The Cognitive Structure of Emotions
Review of The Cognitive Structure of Emotions

The Legacy of Alan Turing and John von Neumann
The Legacy of Alan Turing and John von Neumann

... arguments against the possibility of constructing intelligent machines. ”The reader will have anticipated that I have no very convincing argument of a positive nature to support my views. If I had I should not have taken such pains to point out the fallacies in contrary views. Such evidence as I hav ...
paradigm shift: engineering artificial intelligence and management
paradigm shift: engineering artificial intelligence and management

... Fuzzy rules take facts and determine to what degree the inputted information is true according to that rule. Rules use words and human concepts, rather than strict measurements. These rules can be combined in a process called inference, which can model the real world. Fuzzy logic is currently used t ...
Swarm Intelligence
Swarm Intelligence

... –  one initial user leaves a seed of an idea (a mudball) –  which attracts other users •  who then build upon and modify this initial concept ...
MIT Mobile Robots - What`s Next? - DSpace@MIT
MIT Mobile Robots - What`s Next? - DSpace@MIT

... performed in a distributed fashion. A recently developed light striper vision system will be able to provide depth maps in real time to enable parallel recognition of a number of different types of objects. Each object class has its own special processor to recognize it. When the table-like-object r ...
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Ch1-Introduction

... Neural network research almost disappears Early development of knowledge-based systems AI becomes an industry Neural networks return and became popular AI becomes a science The emergence of intelligent agents AI– CS410, SJTU, 2010 ...
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Client forms DWN

File - The Portfolio of Juliana Madzia
File - The Portfolio of Juliana Madzia

Social Robots: Approaches and Conceptions in the Perspective of
Social Robots: Approaches and Conceptions in the Perspective of

... (and especially its expression in cybernetics, computer science, artificial intelligence theory) and individualism (personal robots), capitalism, with its emphasis on calculations and achieving high efficiency (industrial robots and robotics as business), militarism and politics of war (drones and o ...
Executive Summary - The IEEE Standards Association
Executive Summary - The IEEE Standards Association

... referred to as artificial general intelligence or AGI) may have a transformative effect on the world on the scale of the agricultural or industrial revolutions, which could bring about unprecedented levels of global prosperity. The Safety and Beneficence of Artificial General Intelligence (AGI) and ...
Knowledge Management Systems: Development and Applications Part II: Techniques and Examples
Knowledge Management Systems: Development and Applications Part II: Techniques and Examples

ROC Analysis in Artificial Intelligence
ROC Analysis in Artificial Intelligence

... machine learning, multiagent systems, intelligent decision support and expert systems. In this context, ROC analysis provides techniques to select possibly optimal models and to discard suboptimal ones independently from (and prior to specifying) the cost context or the class distribution. Furthermo ...
Implementation of parallel Optimized ABC Algorithm
Implementation of parallel Optimized ABC Algorithm

... Step.4. For each solution in the local memory Mr of the range processor Pr, determine a neighbor. Step.5. Calculate the optimization for the solutions in Mr. Step.6. Place the onlookers on the food sources in Mr and improve the corresponding solutions (as in step 4). Step.7. Determine the abandoned ...
"Building Knowledge Automation Systems with Exsys CORVID" by
"Building Knowledge Automation Systems with Exsys CORVID" by

... decision-making knowledge and customized recommendations through an interactive interface, rather than just providing facts and data. These types of Web-enabled systems can be integrated into Web sites by a variety of techniques discussed in the book. The systems interact with users in a conversatio ...
ICAISC 2004 Preliminary Program
ICAISC 2004 Preliminary Program

... 1,2m area (A0 or A1 paper size, portrait orientation). Please, do not use just copies of your papers (A4 size). Enlarged version (A3) can be accepted, but printed forms of computer presentations (PowerPoint etc.) or transparencies are preferred at the poster sessions. ...
K5054
K5054

the impact of godel on ai - European Scientific Journal, ESJ
the impact of godel on ai - European Scientific Journal, ESJ

... functions.And again we cite W. Schimanovich who states: ”Recursive programming did not fall from heaven(as some AI people believe today); its development is embedded in a cultural situation produced by a long period of research in mathematics and logic which had been motivated by Godel’s work”. In p ...
Fall Symposium Series
Fall Symposium Series

... his symposium will focus on research issues in developing computational models for integrating language and vision. The intrinsic difficulty of both natural language processing and computer vision has discouraged researchers from attempting integration, although in some cases it may simplify individ ...
Innovative AI Technologies for Future ESA Missions
Innovative AI Technologies for Future ESA Missions

... plan adaptation in case some exogenous events modify the reality. Fault protection, often referred to as Fault Detection, Identification and Recovery (FDIR), is an engineering process that incorporates robustness to faults into spacecraft hardware, software, systems engineering and operations. The o ...
Applications of Signatures to Expert Systems Modelling
Applications of Signatures to Expert Systems Modelling

... literature. Multi-expert models are discussed in [15]. The combination of fuzzy logic, neural networks, genetic algorithms and statistic analysis is analysed in [16]. Reliable rule-based systems with uncertainty are obtained in [17] on the basis of semantic data integration. Model-driven engineering ...
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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.""
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