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... available tools and components, while DSS is often built from scratch Fifth, DSS methodologies and even some tools were developed mostly in the academic world, while BI methodologies and tools were developed mostly by software companies Sixth, many of the tools that BI uses are also considered DSS t ...
tax-based expert systems - University of Southern California
tax-based expert systems - University of Southern California

... symbolic information. Some existing AI languages and ES shells have some inherent problems in processing numeric information, while other computer languages are not as efficient at processing symbolic information. Knowledge bases of tax expert systems are likely to be subject to substantial periodic ...
decision support
decision support

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Workshops Held at the First AAAI Conference on Human
Workshops Held at the First AAAI Conference on Human

... across different scientific areas as one of the most successful strategies to scaling businesses and processes in a rapid and cost effective way. Since 2005 (when Amazon launched its microtask crowdsourcing platform, Mechanical Turk) the community of researchers in computer science, linguistics, spe ...
Quo vadis, computational intelligence
Quo vadis, computational intelligence

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Quo vadis, computational intelligence?
Quo vadis, computational intelligence?

... of artificial intelligence (AI): engineering and empirical science. Traditional AI started as an engineering discipline concerned with the creation of intelligent machines. Computational modeling of human intelligence is an empirical science. Both are based on computations. Artificial Intelligence ( ...
The calculus of self-modifiable algorithms: planning, scheduling and
The calculus of self-modifiable algorithms: planning, scheduling and

... [2-6]) is a universal approach to parallel and intelligent systems, integrating various styles of programming and applied to a wealth of domains of future generation computers. It allows to analyze and design a wide class of systems with intelligence and parallelism. The CSA results suggest that a w ...
Connectionist AI, symbolic AI, and the brain
Connectionist AI, symbolic AI, and the brain

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15.2 ARTIFICIAL INTELLIGENCE (p. 464)
15.2 ARTIFICIAL INTELLIGENCE (p. 464)

Preface May 1996 marks the  tenth  anniversary  of ... That f’n’st  workshop was hosted by the  Qualitative ...
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... restructure the Greek economy, gearing it towards high value added products and services, and achieve the transition to the knowledge economy and society. In formulating this strategy, consideration was given to the revised Lisbon strategy and the need for convergence with the European Union, as wel ...
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Suggested Readings

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Division of Informatics, University of Edinburgh
Division of Informatics, University of Edinburgh

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FROM HERE TO HUMAN-LEVEL AI John McCarthy
FROM HERE TO HUMAN-LEVEL AI John McCarthy

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IJPRAI Call for Papers - Face Recognition Homepage
IJPRAI Call for Papers - Face Recognition Homepage

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agent-based model - IDt
agent-based model - IDt

Candidate for Chair Yolanda Gil University of Southern California
Candidate for Chair Yolanda Gil University of Southern California

... the SIGART team in highlighting such opportunities, providing forums (workshops and maybe even conferences) for discussing research and applications in these areas. It is also important to provide forums at major conferences to help graduate students and early researchers to discuss their research, ...
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PDF

Vasant Dhar
Vasant Dhar

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Alan Turing Biography
Alan Turing Biography

... exhibition was divided into 5 parts, which aim to clarify the relevant aspects of the work of Turing. In the lobby you can watch a video biography of Alan Turing and know the contents available in all areas. There will also be an interactive table with which the visitor can interact with an augmente ...
Reports of the AAAI 2008 Spring Symposia
Reports of the AAAI 2008 Spring Symposia

... reality, and more established AI technologies, such as expert systems. Speakers addressed questions such as what features were necessary for an effective agent-client interaction, diagnostic categories that may benefit from agent-augmented therapy, and ethical and pragmatic issues associated with th ...
Principles of Information Systems, Ninth Edition
Principles of Information Systems, Ninth Edition

... An Overview of Expert Systems • Computerized expert systems – Have been developed to diagnose problems, predict future events, and solve energy problems – Use heuristics, or rules of thumb, to arrive at conclusions or make suggestions ...
The Promise and Perils of Artificial Intelligence
The Promise and Perils of Artificial Intelligence

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ch07 - Home - KSU Faculty Member websites
ch07 - Home - KSU Faculty Member websites

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Artificial Intelligence Informed Search and Exploration
Artificial Intelligence Informed Search and Exploration

... Best-first Search Strategies There is a whole family of best-first search strategies, each with a different evaluation function. Typically, strategies use estimates of the cost of reaching the goal and try to minimize it. Uniform Search also tries to minimize a cost measure. Is it a best-first sear ...
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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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