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Spoken dialogue technology achievements and challenges`` ( file)
Spoken dialogue technology achievements and challenges`` ( file)

... Human factors: performance, usability Tools and languages for design and maintainability Application areas: call centre, enquiries, transactions, healthcare, … ...
white paper from the Workshop on Development and Learning.
white paper from the Workshop on Development and Learning.

A.I. in Power Systems Alarm Processing
A.I. in Power Systems Alarm Processing

... A power system in a metropolitan area can deliver thousands of alarms per day that can overwhelm human operators. This is an alarm stream which, in periods of high inflow, becomes an ’Alarm Avalanche’ or ’Alarm Flood’ and has been around for 25 years since the advent of the Supervisory Control and D ...
Slide 1 - Cal State LA - Cal State LA
Slide 1 - Cal State LA - Cal State LA

... Robot - mechanical device equipped with simulated human senses and the capability of taking action on its own. ...
Reports on the 2012 AAAI Fall Symposium Series
Reports on the 2012 AAAI Fall Symposium Series

... design toy systems capable of generating and detecting jokes as well as deeper concerns about basing the study of humor on a rigorous, formal foundation that would lend itself to computation. AI of humor shares most of the latter efforts but not so much of the former—unless there are interesting ext ...
Review of Reasoning Methods in Clinical Decision Support Systems
Review of Reasoning Methods in Clinical Decision Support Systems

... continuously repeated till the proper solution is discovered. Their advantage is that similar to the neural networks, they derive their knowledge from patient data and the most optimal solution can be achieved, but determining what is the fittest solution is a challenge [4]. From this review it can ...
AI Surveying: Artificial Intelligence In Business
AI Surveying: Artificial Intelligence In Business

... repetitive tasks. It also has the potential to detect patterns of behaviour that would not otherwise be discernable by humans. Many of these applications are found in software that helps managers analyse information so as to derive essential parts and categorize the data. Various AI-based support sy ...
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... July 12-16, 1992. Manuscript submitted January 28, 1992; made available for printing May 13, 1992. ...
Dr. Abeer Mahmoud - PNU-CS-AI
Dr. Abeer Mahmoud - PNU-CS-AI

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Dr. Abeer Mahmoud - PNU-CS-AI
Dr. Abeer Mahmoud - PNU-CS-AI

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Commonsense Reasoning - NYU Computer Science
Commonsense Reasoning - NYU Computer Science

... “Qualitative Physics,” (de Kleer and Brown, 1985), (Kuipers, 1986).) Complex physical systems, particularly artificial devices, can often be effectively analyzed by viewing them as a collections of connected components. In simple cases, the connections between the components remain constant over tim ...
Tilburg University The Nexus between Artificial Intelligence and
Tilburg University The Nexus between Artificial Intelligence and

... paradigm shift in science. While all prior paradigms have been based on an entirely human civilization, AI will create a human-machine civilization. It is likely that during this century the accelerating growth of computer power will result in machine intelligence exceeding human intelligence in cap ...
The Liability Problem for Autonomous Artificial Agents
The Liability Problem for Autonomous Artificial Agents

... the problem (Asaro 2011). It is possible in some criminal situations to hold the people who operate the artificial systems liable, provided you can show intent to commit a crime, or foreseeable risk of a harm rising to the level of criminal negligence. To the extent that artificial agents become inc ...
Artificial Intelligence
Artificial Intelligence

... - Schema.org contains millions of RDF triplets describing known facts: search engines can use this data to provide structured information upon request. - The OpenGraph protocol – which uses RDFa – is used by Facebook to enable any web page to become a rich object in a social graph. Finally, another ...
AI PLANNING FOR TRANSPORTATION LOGISTICS
AI PLANNING FOR TRANSPORTATION LOGISTICS

... The recent evolution of the domain independent heuristic planning started with the work of Drew McDermott ([13], [14]) and the UNPOP planner. The planner is not restricted to pure STRIPS representations, supporting the more expressive ADL language [16]. UNPOP proceeds forwards in the state-space. Es ...
Knowledge Representation in Artificial Intelligence using
Knowledge Representation in Artificial Intelligence using

... Artificial intelligence (AI) is intelligence exhibited by machines. In computer science, the field of AI research defines itself as the study of "intelligent agents". The term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human mind ...
Agent - KDD - Kansas State University
Agent - KDD - Kansas State University

...  Knowledge: represent knowledge about environment  Perception: capability to sense environment  Criterion: performance measure to define degree of success ...
Artificial Intelligence: Modern Approach
Artificial Intelligence: Modern Approach

... annealing, memory-bounded search, global ontologies, dynamic and adaptive probabilistic (Bayesian) networks, computational learning theory, and reinforcement learning. We also provide extensive notes and references on the historical sources and current literature for the main ideas in each chapter. ...
School of Industrial Administration. I did - Stacks
School of Industrial Administration. I did - Stacks

... The methodological imprint described above was central, and the strength of its impression is one of the greatest of the Newell-Simon contributions to the field. Indeed, the concepts that were later to come to primary importance could not be ignored, and were not ignored, during the Genesis period: ...
Computational Intelligence
Computational Intelligence

Slide 1
Slide 1

... • Developed so that users can communicate with computers in human language • Provides question-and-answer setting that’s more natural and easier for people to use • Products aren’t capable of a dialogue that compares with conversations between humans ...
David F pap3 draft1 COMMENTS
David F pap3 draft1 COMMENTS

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Expert Systems 2
Expert Systems 2

... and knowledge to solve a specific problem in a manner superior to others’ (Durkin). • A knowledge engineer is ‘a person who designs, builds and tests an Expert System’ (Durkin). • The end users are the people who will use the expert system. ...
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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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