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Natural Language Processing Regina Barzilay
Natural Language Processing Regina Barzilay

... All the difficult problems in artificial intelligence manifest themselves in NLP problems Turing Test: links machine intelligence with the ability to process language The interrogator C needs to determine which player - A or B - is a computer and which is a human. ...
Apprenticeship Scheduling for Human
Apprenticeship Scheduling for Human

... I have motivated the advantages of autonomous scheduling algorithms in team coordination. The challenge then remains of how we can learn the heuristics and rules-ofthumb of human domain experts to automatically schedule processes. I have personally seen human domain experts who are able to effective ...
Providing Intelligent User-Adapted Control Strategies
Providing Intelligent User-Adapted Control Strategies

... for developing expert systems. Neural network and negotiating agent algorithms have been programmed in C++. The system prototype has been tested in the building of the Ministry of Education, located in the city of Neuquén, Argentina. This building has been designed with a high degree of intelligence ...
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... Introduction to Genetic Algorithms (GA) – Applications of GA in Machine Learning – Machine Learning Approach to Knowledge Acquisition. Objective : To impart knowledge on genetic algorithms and their applications. ...
AI and Education: Celebrating 30 years of Marriage - CEUR
AI and Education: Celebrating 30 years of Marriage - CEUR

... [7] “After all, all smart technologies currently in use (in the classrooms or homes), from tablet computers to smart phones, from Internet search engines to social networking sites, have a growing reliance on techniques derived from AI.” [7] The AI effect began in the larger AI field and “occurs whe ...
PowerPoint
PowerPoint

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CS 561a: Introduction to Artificial Intelligence
CS 561a: Introduction to Artificial Intelligence

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Paper - Asee peer logo
Paper - Asee peer logo

Click Here For
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Micro-Futures - Vic Callaghan
Micro-Futures - Vic Callaghan

... an invited talk at IE’07 (http://www.uni-ulm.de/ie07/), which he duly did, giving a presentation entitled “Do Digital Homes Dream of Electric Families?” - Architecting Consumer Experience“. The pivotal conversation happened at a tavern in the beautiful old German town of Ulm where, after a long day ...
1.5 Impact of emerging technologies
1.5 Impact of emerging technologies

... Artificial intelligence (AI) is computer systems that can simulate human intelligence (able to make decisions typically made by a human). • The PR2 robot is being programmed to complete a number of specific tasks just like a human. • Deep Blue was a chess-playing computer developed by IBM. It is kno ...
application of multiagent systems in transportation
application of multiagent systems in transportation

... 2.3. DISTRIBUTED ARTIFICIAL INTELLIGENCE (DAI) The modern approach to artificial intelligence is centered around the concept of an agent. An agent is a computer system that is situated in some environment, and that is capable of autonomous action in this environment in order to meet its design objec ...
Swarm intelligence
Swarm intelligence

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Application of multi-agent systems and ambient intelligence
Application of multi-agent systems and ambient intelligence

... communication technologies. We can think of two kinds of applications: z centralized knowledge based system or decision support system can simulate dispatcher’s activities and can provide solution his/her task, such as manipulation recommendations, z several task-specific subsystems can be used to s ...
Building Intelligent Interactive Tutors
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Strategic Decision Making
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... After going bankrupt with the failure of his Laugh O Gram Company, Walt Disney decided to rent a camera, assemble an animation stand, and set up a studio in his uncle’s garage. At the age of 21, Walt and his older brother Roy launched the Disney Company in 1923. Their first few films failed and it w ...
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... Software is a key and strategic factor in present-day and future technology and it must be dependable as more or less all of our vital functions depend on it. How is dependability assured? Source of errors: hardware, wired/wireless networks, environment, malicious faults. Fault tolerance and redunda ...
Co-Designing Agents: A Vision
Co-Designing Agents: A Vision

... (a) Answer questions of the form “What would you do in situation x?” (b) Think of situations that may occur, but in which it would not know what to do. Describe the situations, and ask for advice. (c) Discover situations in which it is supposed to do contradictory actions. Describe them, and ask for ...
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Quo vadis, computational intelligence
Quo vadis, computational intelligence

... combinatorial in nature and their solution requires heuristic search techniques. Learning is used to gain knowledge that expert systems may employ for reasoning, and is frequently based on logic. Other branches of computational intelligence are concerned with lower level problems, are more on the pa ...
Machines that dream: A brief introduction into developing artificial
Machines that dream: A brief introduction into developing artificial

... is  being  invested  into  engineering  new  learning  algorithms  and  information  processing   systems.  The  hope  is  that  a  right  set  of  algorithms  will  be  eventually  created  —  making   up  a  machine  that  will  be ...
Quo vadis, computational intelligence?
Quo vadis, computational intelligence?

... topic”. It is obviously a very broad topic now, including good part of neural networks research [5]. In 1982 Hopfield network [26], in 1986 the backpropagation algorithm [49], and a year later the PDP books [7] brought the neural network field to the center of attention. Since that time the field of ...
Mathematical model
Mathematical model

... simulate, in a gross manner, the networks of nerve cell (neurons) of the biological central nervous system. ANNs are an attempt to create machines that work in a similar way to the human brain by building these machines using components that behave like biological neurons, called artificial neurons. ...
The Ethics of Artificial Intelligence
The Ethics of Artificial Intelligence

... algorithms taking over social functions be predictable to those they govern.  To  understand the importance of such predictability, consider an analogy.  The legal  principle of stare decisis binds judges to follow past precedent whenever possible.  To  an engineer, this preference for precedent may ...
Abstract and Biography
Abstract and Biography

... During the past few decades, due to the advances in materials, electronics, and system integration technologies, structural dynamics and controls researchers in various engineering disciplines (e.g., aerospace, civil, mechanical) have been investigating the feasibility of creating adaptive structure ...
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History of artificial intelligence

The history of artificial intelligence (AI) began in antiquity, with myths, stories and rumors of artificial beings endowed with intelligence or consciousness by master craftsmen; as Pamela McCorduck writes, AI began with ""an ancient wish to forge the gods.""The seeds of modern AI were planted by classical philosophers who attempted to describe the process of human thinking as the mechanical manipulation of symbols. This work culminated in the invention of the programmable digital computer in the 1940s, a machine based on the abstract essence of mathematical reasoning. This device and the ideas behind it inspired a handful of scientists to begin seriously discussing the possibility of building an electronic brain.The field of AI research was founded at a conference on the campus of Dartmouth College in the summer of 1956. Those who attended would become the leaders of AI research for decades. Many of them predicted that a machine as intelligent as a human being would exist in no more than a generation and they were given millions of dollars to make this vision come true. Eventually it became obvious that they had grossly underestimated the difficulty of the project. In 1973, in response to the criticism of James Lighthill and ongoing pressure from congress, the U.S. and British Governments stopped funding undirected research into artificial intelligence. Seven years later, a visionary initiative by the Japanese Government inspired governments and industry to provide AI with billions of dollars, but by the late 80s the investors became disillusioned and withdrew funding again. This cycle of boom and bust, of ""AI winters"" and summers, continues to haunt the field. Undaunted, there are those who make extraordinary predictions even now.Progress in AI has continued, despite the rise and fall of its reputation in the eyes of government bureaucrats and venture capitalists. Problems that had begun to seem impossible in 1970 have been solved and the solutions are now used in successful commercial products. However, no machine has been built with a human level of intelligence, contrary to the optimistic predictions of the first generation of AI researchers. ""We can only see a short distance ahead,"" admitted Alan Turing, in a famous 1950 paper that catalyzed the modern search for machines that think. ""But,"" he added, ""we can see much that must be done.""
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