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NRC 39221
NRC 39221

(Lehigh U.) on image understanding, web security and CAPTCHAS
(Lehigh U.) on image understanding, web security and CAPTCHAS

... Udi Manber asked Prof. Manuel Blum’s group at CMS-SCS: – programs impersonate people in chat rooms, then hand out ads – ugh! – how can all machines be denied access to a Web site without inconveniencing any human users? I.e., how to distinguish between machines and people on-line … some variation on ...
Survey of Applications Integrating Constraint Satisfaction and Case
Survey of Applications Integrating Constraint Satisfaction and Case

... capturing the rules from which the system can reason. Rule acquisition can be a time consuming and unreliable process. CBR makes it unnecessary to formulate experiences into rules. Some problem domains in particular naturally provide cases as part of the standard problem-solving process. Other domai ...
Connectionism and Information Processing Abstractions
Connectionism and Information Processing Abstractions

... Challenge to the Symbolic View Much of the theoretical and empirical research in AI over the past 30 years has been based on the so-called symbolic paradigm—the thesis that algorithmic processes which interpret discrete symbol systems provide a good basis for modeling human cognition. Stronger versi ...
Contextualizing Reflective Dialogue in a Spoken Conversational Tutor
Contextualizing Reflective Dialogue in a Spoken Conversational Tutor

Reasoning about Action and Cooperation
Reasoning about Action and Cooperation

... The cooperation modality of Coalition Logic expresses the ability of a group to obtain a certain state of affairs. This kind of expression can now be analysed using the two modules described above: a group G of agents has the ability to obtain a state of affairs φ just in case there exists a plan β ...
Strategies and Design for Interleaving Reasoning and Selection of Axioms
Strategies and Design for Interleaving Reasoning and Selection of Axioms

... Anytime algorithms are attractive for Web scale reasoning, because they allow a trade-off between the cost of the algorithm and the quality of the results. Such anytime algorithms have been developed for many AI reasoning tasks, such as planning, diagnosis and search. However, until now no anytime m ...
Uncertainty reasoning and representation: A
Uncertainty reasoning and representation: A

... with ...
MACHINE FASHION: AN ARTIFICIAL INTELLIGENCE BASED
MACHINE FASHION: AN ARTIFICIAL INTELLIGENCE BASED

... Human creativity as one of the major challenges for the AI domain has captured the world’s attention for years. Artist Harold Cohen’s AI artist program, “AARON”, was the first profound connection between AI and human creativity and has been in continual development since its creation in 1937 (Cohen, ...
Step back and look at the History of AI
Step back and look at the History of AI

... because it is usually reserved for inmates on parole. Martial Leconte, considered dangerous pedophile, has agreed to wear the bracelet for at least two years. This is a first in France . An inmate, sentenced in 1998 to 14 years in prison for the rape of a schoolgirl 11 years, has pledged to bring an ...
Dynamic Restart Policies - Association for the Advancement of
Dynamic Restart Policies - Association for the Advancement of

... to variable ratio in a SAT instance, as has been long considered in work on random k-SAT (Mitchell et al. 1992; Selman & Kirkpatrick 1996). Dynamic features are measurements obtained via the process of problem solving; they are observations of a search algorithm’s state while it is in the process of ...
Dynamic Restart Policies
Dynamic Restart Policies

... to variable ratio in a SAT instance, as has been long considered in work on random k-SAT (Mitchell et al. 1992; Selman & Kirkpatrick 1996). Dynamic features are measurements obtained via the process of problem solving; they are observations of a search algorithm’s state while it is in the process of ...
Artificial Intelligence
Artificial Intelligence

... Humans, it seems, know things and do reasoning. Knowledge and reasoning are also important for artificial agents because they enable successful behaviors that would be very hard to achieve otherwise. We have seen that knowledge of action outcomes enables problemsolving agents to perform well in comp ...
Selforganizology: A more detailed description
Selforganizology: A more detailed description

... and adaptively adjust the search direction without determinant rules. These properties make genetic algorithm widely use in combinatorial optimization, machine learning, signal processing, adaptive control and artificial life. Genetic algorithm is considered key technology that will significantly im ...
A preliminary analysis of the Soar architecture as a basis for general
A preliminary analysis of the Soar architecture as a basis for general

... been shared by a large segment of the cognitive science community; it is not, however, shared by the connectionist community, which focuses on the neural band (plus the lower levels of the cognitive band), or by the logicist and expert-systems communities, which focus on the rational band. This assu ...
How Robots Work
How Robots Work

... language and the ability to formulate original ideas. Roboticists are nowhere near achieving this level of artificial intelligence, but they have made a lot of progress with more limited AI. Today's AI machines can replicate some specific elements of intellectual ability. Computers can already solve ...
A Study on Swarm Intelligence Techniques in Intrusion Detection
A Study on Swarm Intelligence Techniques in Intrusion Detection

... At the same time it decreases for all other terms (evaporation). Among the discovered rules the best one is selected and augmented to the discovered rules. This is done iteratively until a large base of rules is constructed which can be later on used in test sets as criteria for classifying network ...
The Twenty-Ninth International Florida Artificial Intelligence
The Twenty-Ninth International Florida Artificial Intelligence

... Our General Conference Invited Keynote Speakers are Sumi Helal (University of Florida, USA), Matthew Johnson (Florida Institute for Human & Machine Cognition, USA), and Kristin Tolle (Microsoft Research Outreach, USA). In addition, our Special Track Invited Speakers are Diana Inkpen (University of O ...
Artificial Intelligence and Humor
Artificial Intelligence and Humor

pdf file
pdf file

... In most real-life situations humans receive information that can be interpreted in many different ways. On the one hand this involves interpretation: the information from the outside world has to be given a meaning. In logic the notion of interpretation mapping has been introduced to describe the in ...
Enactive Artificial Intelligence
Enactive Artificial Intelligence

... embodiment and situatedness in behavior-based AI and robotics in the late 1980s (e.g. Brooks 1991) has continued to be further developed (e.g. Brooks 1997; Arkin 1998; Pfeifer & Bongard 2007) and has considerably influenced the emergence of a variety of successful AI research programs such as, for e ...
pdf
pdf

... multi-agent systems, cognitive modelling and ambient intelligence. Catholijn Jonker (1967) is a Full Professor of Man-Machine Interaction at the Faculty of Electrical Engineering, Mathematics and Computer Science of the Delft University of Technology, the Netherlands. She studied Computer Science an ...
Baseball Prediction Using Ensemble Learning by Arlo Lyle (Under
Baseball Prediction Using Ensemble Learning by Arlo Lyle (Under

GNU/Linux AI & Alife HOWTO
GNU/Linux AI & Alife HOWTO

... Basically, the library offers the programmer a set of search algorithms that may be used to solve all kind of different problems. The idea is that when developing problem solving software the programmer should be able to concentrate on the representation of the problem to be solved and should not ne ...
Artificial Intelligence Illuminated
Artificial Intelligence Illuminated

... or students of other subjects that cover Artificial Intelligence. It also is intended to be an interesting and relevant introduction to the subject for other students or individuals who simply have an interest in the subject. The book assumes very little knowledge of computer science, but does assum ...
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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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