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Artificial Intelligence
Artificial Intelligence

... on the human sciences as a basis for an understanding of human functioning and wellbeing. As a bridge between these two streams the so-called modelling stream ties them together which aims to achieve the depth that is required to analyse and design scientifically justifiable smart systems. The commi ...
Artificial Cognitive Systems
Artificial Cognitive Systems

... Cognitive Systems Monographs (COSMOS), Vol. 11, Springer Chapter 5 and Appendix I (20 cognitive architectures) David Vernon, Artificial Cognitive Systems – A Primer, MIT Press, 2014 ...
word office version - European Parliament
word office version - European Parliament

... omissions of robots which have caused harm could have been avoided; AC. whereas, ultimately, the autonomy of robots raises the question of their nature in the light of the existing legal categories or whether a new category should be created, with its own specific features and implications; AD. wher ...
comparative study of case based reasoning software
comparative study of case based reasoning software

... This section introduces a comparative study after testing and comparing the CBR applications mentioned previously in table 1 using the same case base. The case base used for testing the previously mentioned software obtained from the UC Irvine Machine Learning Repository which contains details for 1 ...
Chapter 13: Advances in Computing
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The Intelligence of Dual Simplex Method to Solve Linear Fractional
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AAAI News - Association for the Advancement of Artificial Intelligence
AAAI News - Association for the Advancement of Artificial Intelligence

... year for extraordinary service to the AI community. The AAAI Awards Committee is pleased to announce that the first recipient of this award was Barbara J. Grosz, Gordon McKay professor of computer science at Harvard University and a past president of AAAI. Grosz was honored for her contributions to ...
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User-centric query refinement and processing using granularity

... Starting point · Multi-level completeness · Multi-level specificity · Multiple perspectives ...
Artificial Intelligence and Operations Research
Artificial Intelligence and Operations Research

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Welcome to IJCAI 2015!
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Constraints and AI Planning

... Once we model a problem, we can employ different search techniques to extract a solution. The most common is a treebased refinement search, which, unlike branch-and-bound (see the main article), doesn’t apply continuous relaxations. Instead, it applies at all decision nodes a variety of branch selec ...
Creating New Pathways to Justice Using Simple Artificial
Creating New Pathways to Justice Using Simple Artificial

... My description of the JPES is meant to contribute to literature concerned with the disciplines of information technology, law and ODR. These descriptions are offered at a conceptual level and are neither strictly legalistic nor techno‐ cratic. Part of this effort is concerned with taking concepts fr ...
Artificial Intelligence
Artificial Intelligence

... This report reflects the findings and considerations of the panel on the master’s programme in Artificial Intelligence at Radboud University Nijmegen. The evaluation of the panel is based on information provided in the critical reflection and the selected theses, additional documentation and intervi ...
Artificial Intelligence
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... allows propagation of uncertainties along extended chains of reasoning, and eases implementation of large knowledge bases. Several techniques for representing uncertainty in expert systems have been proposed in the AI literature including Bayesian analysis and certainty measures [4]. For the most p ...
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... expressed in a specific medium in order to extract information that will give more accurate specifications for the analysis of information in another medium. Integration takes place mainly when the output of the analysis of one medium is used for constraining or even guiding the analysis of another ...
Advances in conversational case-based reasoning
Advances in conversational case-based reasoning

... (2001). Instead, McSherry (2003, 2005a,b) proposes a goal-driven approach to question selection in which the relevance of questions the user is asked can be explained in terms of the system’s strategy of confirming a target case as the recommended case. ...
Artificial Intelligence
Artificial Intelligence

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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(生物的), based on the idea that since humans are intelligent, AI should study humans and imitate their psychology or physiolog ...
Heuristic Search Comes of Age
Heuristic Search Comes of Age

... goal state. This describes puzzles like Rubik’s cube or the sliding-tile puzzle. A different model of a search problem is found in the video game industry. In this industry search is used to plan character movement in virtual worlds. The entire search graph representing the world usually fits in mem ...
sequential decision models for expert system optimization
sequential decision models for expert system optimization

Laboratorio di Intelligenza Artificiale e Robotica
Laboratorio di Intelligenza Artificiale e Robotica

... ‰ Daniele Loiacono ...
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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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