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Paper  - IFIS Uni Lübeck
Paper - IFIS Uni Lübeck

... effectively, it was found that nominals (concepts representing single domain objects as defined in the DL SHOIQ [49]) were not of utmost importance for RacerPro users [43]. In many cases, in which users initially wanted nominals, strings were found to be sufficient. Furthermore, since multiple Aboxe ...
Advances in Artificial Intelligence Using Speech Recognition
Advances in Artificial Intelligence Using Speech Recognition

... study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and h ...
THE CHALLENGE OF INTELLIGENT SYSTEMS
THE CHALLENGE OF INTELLIGENT SYSTEMS

... be understood. The understanding of each other’s work can facilitate better progress in the field overall. Performance measures for intelligent controllers can begin to be developed, providing benchmarks for system performance and helping users and designers of systems better understand the benefits ...
Artificial Participation: An Interview with Warren Sack* Preface: Joseph Dumit
Artificial Participation: An Interview with Warren Sack* Preface: Joseph Dumit

... built is a computational, critical mirror. These Sophistic, computer technologies of (dis)simulation just reflect people’s comments back at them. They are more interesting than a simple parroting though because they amplify certain words or comments. I think this is what various experiments in theat ...
AAAI Fall Symposium Series - Association for the Advancement of
AAAI Fall Symposium Series - Association for the Advancement of

... tasks autonomously in the real world has long been a goal of artificial intelligence research. While a great deal of progress has been made towards this goal in recent years, there is still a wide gap between what theorists claim should be possible and what has been functionally demonstrated on robo ...
GRANULAR COMPUTING: A NEW PARADIGM IN INFORMATION
GRANULAR COMPUTING: A NEW PARADIGM IN INFORMATION

... the fastest growing information processing paradigm in computational intelligence and human-centric systems. It has been gaining popularity in the past ten years. GrC is often loosely defined as an umbrella term to cover any theories, methodologies, techniques, and tools that make use of granules in ...
this PDF file - BRAIN. Broad Research in Artificial
this PDF file - BRAIN. Broad Research in Artificial

... density of clusters, occurrence of local minima of the log likelihood, and their sensitiveness to initialization of model parameters, for example the mean and the std. deviation in case of the Gaussian mixtures [4]. Several stochastic models have been reported to deal with the limitations of the gen ...
PDF only
PDF only

... have already proven to be useful in many appli­ cations, this paper contends that they do not go far enough in meeting the requirements of current knowledge based systems. In particular, these tools force the user to represent all of the knowledge rel­ evant to a problem in the same knowledge repres ...
Reinforcement Learning and the Reward Engineering Principle
Reinforcement Learning and the Reward Engineering Principle

... more reliable, perhaps even removing a human from the loop altogether and giving rewards via an automatic mechanism. Call this type of effort reward engineering; the reinforcement learning agent’s goal is not being changed, but the environment is being partially designed so that reward maximization ...
Complete Issue
Complete Issue

... Reasoning, Evolutionary and Swarm Algorithms and Expert System Development Stages, Fuzzy Sets and logic and Knowledge-Based Systems, Problem solving Methods Self-Healing and Autonomous Systems etc. The initial efforts helped to shape the editorial policy and to sharpen the focus of the journal. Star ...
A Comparative Utility Analysis of Case
A Comparative Utility Analysis of Case

... Given a particular evaluation metric, the utility of a learned item can be defined as the change in expectation values of a problem solver's performance on the metric across a problem set (MARKOVITCH & SCOTT 1993). In other words, when we compute the utility of a change to the system's knowledge bas ...
Heuristic Search
Heuristic Search

... Issues in Heuristic Search •Searching using heuristic function does not solely on directed solution  but the best algorithm to find shortest path towards goal. •Admissible  attempt to find possible shortest path to a goal whenever it exists. •Informedness  question in what sense the heuristic fu ...
information society technologies
information society technologies

... systems that exhibit intelligent behaviour. While cognitive systems may derive inspiration from biological intelligence, Cognitive Systems is a separte scientific discipline, concerning artificial systems [Simon 87] that combine perception, action and reasoning. As a scientific discipline, Cognitive ...
Beyond AI: Artificial Dreams
Beyond AI: Artificial Dreams

... that cannot be reasoned with and which are capable of producing action. To put it differently, whether something is to be considered as a true desire depends solely on its detachment from reasoning process and simultaneously on its ability to trigger an action.4 This new distinction between desires ...
Eleanor Dare - Department of Computing
Eleanor Dare - Department of Computing

... Wendy Hollway expands upon the theme of the non-rational, nonunitary individual. Such an individual is complex and contradictory and represents a critique of Foucauldian genealogies, which Hollway interprets as framing subjectivities ‘as merely the sum total of positions occupied in discourses by a ...
Intelligent Software Environment for Integrated Expert Systems
Intelligent Software Environment for Integrated Expert Systems

... Today automatic generation of plans by a software and hardware system is often meant as the intelligent planning, but the term “intelligent planning”» has no clear definition. For example, the term “intelligent planning” is more commonly used in Russian literature [15], while “automated planning” is ...
Logical Formal Description of Expert Systems
Logical Formal Description of Expert Systems

... Abstract. The objective of expert systems is the use of Artificial Intelligence tools so as to solve problems within specific prefixed applications. Even when such systems are widely applied in diverse applications, as manufacturing or control systems, until now, there is an important gap in the dev ...
McLeod_CH11
McLeod_CH11

... Gorry and Scott Morton (1971) argued that an information system that focused on single problems faced by single managers would provide better support. Central to their concept was a table, called the Gorry-Scott Morton grid (Figure 11.2) that classifies problems in terms of problem structure and man ...
Chapter 18
Chapter 18

... Several Real-world Applications of ANN Technology Two Decision Support Technologies: – Genetic Algorithms – Fuzzy Logic ...
Lessons from The Turing Test - Cognitive Science Department
Lessons from The Turing Test - Cognitive Science Department

... machine ‘as a whole’: the machine solving problems, answering questions, etc. ...
Artificial Intelligence Winter 2004
Artificial Intelligence Winter 2004

... certain precise temperature (which may not be known or may not be of interest).  In a subjective situation there is no exact original (like “this is stupid”), only a subjective impression is reflected.  In order put subjective vagueness on solid foundations the reasoning in the model is replaced b ...
Case-Based Reasoning and Expert Systems
Case-Based Reasoning and Expert Systems

... Besides describing our own activities on this level of detail together with our concrete implementations - we are also looking for collaboration partners We already collaborate with University of West London (Th. RothBerghofer) with respect to explanation awareness ...
How Insurers Can Harness Artificial Intelligence
How Insurers Can Harness Artificial Intelligence

... At its essence, AI is about embedding human intelligence into machines, enabling systems to learn, adapt and develop solutions to problems on their own. Various AI-related technologies, such as natural language processing (NLP), computer vision, robotics, machine learning and speech recognition, hav ...
Word - The Open University
Word - The Open University

... built? It's obvious that most of the examples I found were seen by their makers, and probably by the public too, simply as curiosities. One reason for building such lifelike machines, then, would have been to amuse, amaze, and milk money from the credulous – as in the case of the chess automata, or ...
THE ROLES AND GOALS OF INFORMATION TECHNOLOGY
THE ROLES AND GOALS OF INFORMATION TECHNOLOGY

...  Many companies start out with e-mail and then expand their collaboration systems to include many other features.  Some of these features include tele- video- and Web-conferencing, as well as project management and work flow automation. Concept Reinforcement: Adding Value – Class Participation  A ...
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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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