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ILP turns 20 | SpringerLink
ILP turns 20 | SpringerLink

... In order to understand the development of ILP as a research area, it is important to reflect on its origins in and relationship with Logic Programming, which emerged as a declarative programming paradigm in the 1970s and became influential in the 1980s. Although it was customary to describe ILP as a ...
Discrete Event Calculus Deduction using First
Discrete Event Calculus Deduction using First

... theorem proving (ATP) systems [11] to solve event calculus reasoning problems. To our knowledge, this is the first time this has been done. We limit ourselves here to discrete time. Our long-term goal is to develop a collection of systems for solving event calculus reasoning problems, both discrete ...
Converging on the Divergent - Association for Computational
Converging on the Divergent - Association for Computational

... computational creativity is not a solution to a particular problem, like many of the current agreed grand challenges in AI. Rather, it is likely to be the way a system does what it does, and how well, that constitutes the real challenge. For example, one less-than-grand challenge to overcome is the ...
Applications of Artificial Intelligence
Applications of Artificial Intelligence

... I propose to consider the question "Can machines think ?“ AG Bio-/ Medizinische-Informatik ...
Analyzing Impact of AI Tools on Traditional Workflow Systems
Analyzing Impact of AI Tools on Traditional Workflow Systems

... Various researchers provides different definition of AI but all definitions says more or less the same thing, which includes the use of heuristic techniques to solve the complex problems with the help of different computational models, the art of creating intelligent machines which can learn, think ...
INTRODUCTION TO Al AND PRODUCTION SYSTEMS 9
INTRODUCTION TO Al AND PRODUCTION SYSTEMS 9

F10 - IDt
F10 - IDt

... 1954 (7 June): Death (suicide) by cyanide poisoning, Wilmslow, Cheshire. ...
What is AI?
What is AI?

... Neural network research almost disappears Early development of knowledge-based systems AI becomes an industry Neural networks return to popularity AI becomes a science The emergence of intelligent agents CS 331: Dr M M Awais (LUMS) ...
Curriculum Vitae - People.csail.mit.edu
Curriculum Vitae - People.csail.mit.edu

... With advisor Leslie Pack Kaelbling, developing a modern cognitive architecture. The driving application in mind is to develop software-based secretaries that understand their bosses’ habits and can carry out their wishes automatically. Research Assistant, Institute for Computer Science, Albert-Ludwi ...
Program booklet
Program booklet

... In addition to these special presentations, IJCAI’s regular track features 413 papers, selected from 1,473 submissions. All papers are presented as a poster, and 195 of them will also be presented orally in parallel conference sessions. IJCAI features 10 plenary talks, comprised of 8 invited keynote ...
Intelligent Vehicles
Intelligent Vehicles

... Intelligent Environments ...
MANAGING KNOWLEDGE
MANAGING KNOWLEDGE

Expertise transfer and complex problems" using AQUINAS as a
Expertise transfer and complex problems" using AQUINAS as a

... Hierarchies in Aquinas are organized around solutions, traits, knowledge sources (i.e. experts), and cases. Nodes in the four hierarchies combine to form rating grids. In the most simple case, the children of a node in a solution hierarchy supply the solutions along the top of a grid; the children o ...
Curriculum Vitae - University of Pittsburgh School of Law
Curriculum Vitae - University of Pittsburgh School of Law

... Learning Research and Development Center Internal Grant entitled “Improving Learning from Peer Review with NLP and ITS techniques” ($150,000) 2009-2010. With Chris Schunn and Diane Litman. Learning Research and Development Center Internal Grant entitled “Measuring Classroom Discussions in Mathematic ...
implementing a decision support system for online job seeking
implementing a decision support system for online job seeking

... extend along a single dimension, ranging from extremely data-oriented to extremely modeloriented. Alter conducted a field study of 56 DSS that he categorized into seven distinct types of DSS. His seven types include: File drawer systems that provide access to data items. Data analysis systems that s ...
(IT) in Knowledge Management
(IT) in Knowledge Management

... Scan e-mail, documents, and databases to perform knowledge discovery, determine meaningful relationships and rules Identify patterns in data (usually through neural networks and other data mining techniques) Forecast future results by using data/knowledge Provide advice directly from knowledge by us ...
AI in chemometrics
AI in chemometrics

... machines, which way of acting can be considered as „human” (caused by „human” intelligence) ...
Intelligent Agents
Intelligent Agents

... capable of flexible autonomous action to meet its design objectives. Flexible means: reactivity: intelligent agents perceive and respond in a timely fashion to changes that occur in their environment in order to satisfy their design objectives. The agent’s goals and/or assumptions that form the basi ...
KBS - teachmath1729
KBS - teachmath1729

... * efficiency in choosing path to reach the goal * GPS did not use specific info about problem at hand in selection of state transition * GPS examined all states leading to exponential time complexity * breakthrough in AI towards more specialised problem-solving system, i.e., Knowledge-based systems ...
The 2004 Mobile Robot Competition and Exhibition
The 2004 Mobile Robot Competition and Exhibition

... demonstrate comprehensive emergency response scenarios. Overall, the competition goals were achieved this year by evaluating state-of-the-art technologies, methods, and algorithms applied to search and rescue robots through objective testing in relevant environments, statistically significant repeti ...
Chapter 4 - High Point University
Chapter 4 - High Point University

... • monitoring and surveillance agents – monitor network for likely problems ...
Main Areas of AI
Main Areas of AI

... • If computers are intelligent what civil rights should be given to computers? • If computers can perform most of our work; what should the human beings do? • Only those things that can be represented in computers are important. • It is fun to play with computers. ...
Artificial Intelligence Question Bank 2014
Artificial Intelligence Question Bank 2014

... How default logic helps in reasoning? Explain. What are the problems which occur on default reasoning? Define Default reasoning and state all its features. What do we mean by the term Closed World Assumption? Elaborate with an example. Explain the framework of MBR. What are the disadvantages of Rule ...
Robin Douglas Burke Associate Professor
Robin Douglas Burke Associate Professor

... on component technology. Spring 2001. E-Commerce – Technical Perspective.* Technical foundations of electronic commerce. Spring, Fall 2001. Java for Business.* Introductory Java programming with business emphasis. Fall 2001. University of California, Irvine Honors Data Structures and Algorithms. Int ...
Robotics, Temporal Logic and Stream Reasoning
Robotics, Temporal Logic and Stream Reasoning

... A related issue of fundamental importance is the principled management of dataflow in such architectures. This issue is often overlooked, but is central to the ability of a system to reason at a high level of abstraction in a semantically grounded and qualitative manner. Control, reactive and delibe ...
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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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