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Probabilistic graphical models in artificial intelligence
Probabilistic graphical models in artificial intelligence

... methods mainly based on intuition. This was the case of INTERNIST-1 [6]. Some of these suffered from important inconsistencies, mainly due to the non-distinction between absolute and updated beliefs (beliefs that are obtained under certain given observations). This was also the case of INFERNO [7]. ...
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... In this paper, we discuss how reinforcement learning techniques of developing policies to optimize environmental feedback, through a mapping between perceptions and actions, can be used by multiple agents to learn coordination strategies without having to rely on shared information. These agents, th ...
Solving the Round Robin Problem Using Propositional Logic
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... In sports scheduling one of the issues is to find a feasible schedule for a sports league that takes into consideration constraints on how the competing teams can be paired, as well as how each team’s games are distributed in the entire schedule. Here we consider the timetabling problem for the clas ...
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... to the manager role and situation model. It may suggest new goals, alternative decisions or elaborate plans of the intervention. Intelligent agent can use various Artificial Intelligent methods which enable to copy with uncertain and incomplete data, qualitative reasoning, constrains satisfactions a ...
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Applications of Artificial Intelligence in Machine Learning: Review

... Machine learning is one of the most exciting recent technologies in Artificial Intelligence. Learning algorithms in many applications that’s we make use of daily. Every time a web search engine like Google or Bing is used to search the internet, one of the reasons that works so well is because a lea ...
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Expert Systems - Myreaders.info

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... were added each day in 2009. An average of 607 police reports were filed each day, totaling in 221 708 for the whole year, in the Västra Götaland region of Sweden alone1. The Swedish police have a clear directive to work against ‘crimes of quantity’, such as burglary, physical abuse, vandalism and m ...
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... Overview of Artificial Life The phrase “artificial life” was coined by Christopher Langton. He envisioned a study of life as it could be in any possible setting, and he organized the first conference that explicitly recognized this field (Langton 1989). There has since been a regular series of confe ...
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First-Order Logic

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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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