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Building a Cultural Intelligence Decision Support System - R
Building a Cultural Intelligence Decision Support System - R

... work environment. In addition, traditional business intelligence (BI) has encountered two challenges: the first involves determining the means of adapting to cultural diversity; the second pertains to treating cultural soft data for decision making [6]. Our claim is that when CQ is applied to indivi ...
A Review of Decision Support Systems for - CEUR
A Review of Decision Support Systems for - CEUR

... Decision support systems (DSS) are about developing and deploying IT-based systems to support decision processes [5, 30]. Since the 1970s researchers,have focused on developing computer technology based solutions that can be used to support complex decision-making and problem solving [31]. The area ...
CS 561a: Introduction to Artificial Intelligence
CS 561a: Introduction to Artificial Intelligence

... • AI research has both theoretical and experimental sides. The experimental side has both basic and applied aspects. • There are two main lines of research: • One is biological, based on the idea that since humans are intelligent, AI should study humans and imitate their psychology or physiology. • ...
Risk-based estimation of manufacturing order costs with artificial
Risk-based estimation of manufacturing order costs with artificial

... stage provide the core for the fuzzy inference system [16]. Apart from the reasoning rules, this method requires selection of suitable inputs, membership functions and defuzzification. The short descriptions of each method indicate clearly that each model is burdened with certain limitations of diff ...
CS 460: Artificial Intelligence
CS 460: Artificial Intelligence

... • AI research has both theoretical and experimental sides. The experimental side has both basic and applied aspects. • There are two main lines of research: • One is biological, based on the idea that since humans are intelligent, AI should study humans and imitate their psychology or physiology. • ...
session01
session01

... • AI research has both theoretical and experimental sides. The experimental side has both basic and applied aspects. • There are two main lines of research: • One is biological, based on the idea that since humans are intelligent, AI should study humans and imitate their psychology or physiology. • ...
AAAI Proceedings Template - Advances in Cognitive Systems
AAAI Proceedings Template - Advances in Cognitive Systems

... An early success of Watson commercialization is medical treatment suggestion at Memorial Sloan Kettering Cancer Center (Kelly & Hamm, 2013). Watson was trained with hundreds of thousands of pieces of medical evidence, millions of pages of text, 25,000 training cases, and over 14,000 person-hours of ...
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... • AI research has both theoretical and experimental sides. The experimental side has both basic and applied aspects. • There are two main lines of research: • One is biological, based on the idea that since humans are intelligent, AI should study humans and imitate their psychology or physiology. • ...
The Effect of Applying Artificial Intelligence in Shaping Marketing
The Effect of Applying Artificial Intelligence in Shaping Marketing

... generate high quality administrative decisions contrary to other traditional systems. The study of Abdil-Majeed, KutaibahMazen, (2009) aimed at identifying the effect of using artificial intelligence in electrical engineering applications. The study showed that the neural network tends to modeling t ...
Probabilistic Reasoning and the Design of Expert Systems
Probabilistic Reasoning and the Design of Expert Systems

... would be expressed in the links between it and its parent states) made BBN reasoning quite manageable computationally. In recent years the use of graphical models has replaced the traditional expert system, especially in situations where reasoning was diagnostic and prognostic, i.e., extending from ...
study of difference between forward and backward reasoning
study of difference between forward and backward reasoning

... THEN clause that matches a desired goal. If the IF clause of that inference rule is not known to be true, then it is added to the list of goals (in order for goal to be confirmed it must also provide data that confirms this new rule) [4]. In other words, this approach starts with the desired conclus ...
law and ethics for autonomous weapon systems
law and ethics for autonomous weapon systems

Integrated Maintenance with Case Factories for - CEUR
Integrated Maintenance with Case Factories for - CEUR

... dependencies between these knowledge sources as well as high-level maintenance goals. An example is removing one or more cases from a case base. Cases in other CBR systems could depend on one of the removed cases, so they may become inconsistent (to some degree). The system should suggest an appropr ...
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... real world domain contain very valuable planning knowledge. In order to make this compiled knowledge re-usable for novel situations, a specific integrated knowledge acquisition method has been developed: First, a domain theory is established from documentation materials or texts, which is then used ...
curriculum vitae - Menkes van den Briel
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... Aircraft Boarding Fine-Tuning. In Proceedings of the 14th International Conference on Industrial Engineering and Operations Management (ICIEOM). M.H.L. van den Briel, J. Benton, S. Kambhampati, and T. Vossen (2007), LP-Based Heuristic for Optimal Planning. In Proceedings of the 13th International Co ...
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Artificial Intelligence (AI): Trying to Get Computers to Think Like Us
Artificial Intelligence (AI): Trying to Get Computers to Think Like Us

... Abstract AI is a field older than most realize – the term was coined in the mid 1950s. The field is comprised of many subfields but the main focus is on building intelligent entities. In order to achieve this goal many subcomponents need to be built, including methods for assisting computers to thi ...
Uncertainty Handling for Sensor Location Estimation in Wireless
Uncertainty Handling for Sensor Location Estimation in Wireless

... 1. Introduction Recent advances in hardware miniaturization and communication technologies have led to the emergence of Wireless Sensor Networks (WSN). A WSN consists of small, inexpensive, battery-powered, and wirelessly connected sensors which are usually employed for distributed sensing of physic ...
Nineteenth National Conference on Artificial Intelligence Calls for Papers, Proposals, &
Nineteenth National Conference on Artificial Intelligence Calls for Papers, Proposals, &

... is the Nineteenth National Conference on Artificial Intelligence (AI). The purpose of this conference is to promote research in AI and scientific interchange among AI researchers, practitioners, and scientists and engineers in related disciplines. AAAI-04 will have multiple technical tracks, poster ...
hybrid expert system agents - Universitatea"Petru Maior"
hybrid expert system agents - Universitatea"Petru Maior"

... agents. A hybrid expert system agent can solve efficiently a large variety of problems. A neural network component of a hybrid expert system agent solves problems like the neural networks. Hybrid expert system agent that uses neural network components has advantages in the problems solving versus th ...
CS 561a: Introduction to Artificial Intelligence
CS 561a: Introduction to Artificial Intelligence

... • AI research has both theoretical and experimental sides. The experimental side has both basic and applied aspects. • There are two main lines of research: • One is biological, based on the idea that since humans are intelligent, AI should study humans and imitate their psychology or physiology. • ...
AI Reloaded: Objectives, Potentials, and Challenges of the Novel
AI Reloaded: Objectives, Potentials, and Challenges of the Novel

... literature. These circumstances of course do not contribute to an acceleration of the developments in this field. To overcome this problem, this article aims to provide a first comprehensive review on this young domain of science. Although it might happen that certain other researchers of this so fa ...
Rational Artificial Intelligence for the Greater Good - Self
Rational Artificial Intelligence for the Greater Good - Self

... shift from being purely “reactive” to being “deliberative”. They begin to build models of their environments and to choose actions by reasoning about those models. They develop episodic memory which is used in the construction of their models. At first the models are crude and highly stochastic but ...
Artificial Intelligence and Expert Systems
Artificial Intelligence and Expert Systems

... General problem solvers cannot be used to build high performance ES Human problem solvers are good only if they operate in a very narrow domain Expert systems must be constantly updated with new information The complexity of problems requires a considerable amount of knowledge about the problem area ...
A SURVEY OF THE APPLICATION OF MACHINE LEARNING IN
A SURVEY OF THE APPLICATION OF MACHINE LEARNING IN

... The emergence of the DSS research stream is based upon the idea of using computers for supporting decision-makers (Bonini, 1963). The work of Gorry and Scott Morton (1971) is one of the foundations of the DSS academic area. In their work, they introduced a framework for managerial decision-making su ...
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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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