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How We`re Predicting AI—or Failing To
How We`re Predicting AI—or Failing To

Translation of Aggregate Programs to Normal Logic Programs
Translation of Aggregate Programs to Normal Logic Programs

... In two papers [5, 11] we defined partial stable semantics for logic programs with arbitrary aggregate relations. The semantics are based on Approximation Theory [3, 4] which provides a solid algebraic framework for defining non-monotonic semantics. The ultimate well-founded and stable semantics of a ...
Heuristic Search Comes of Age
Heuristic Search Comes of Age

... heuristics would arise in practice. The understanding of inconsistent heuristics has been greatly increased (Felner et al. 2011). It is now understood that inconsistent heuristics are easy to build and can be quite beneficial in practice. The drawbacks previously studied do not apply to algorithms l ...
ppt
ppt

... What lessons for robots from these alternative views? At first sight, they are negative and unhelpful ! For everyday robot actions this implies we should do without planning, without the computational model, without internal representations ... .... but what should we do instead ? Non-Symbolic AI le ...
Dialogue Tools and Negotiation Support Systems in a Three-Step
Dialogue Tools and Negotiation Support Systems in a Three-Step

... Although some systems operating on small, straightforward legal domains proved successful, the AI & Law community realized that developing legal expert systems was far more complicated than it first appreciated. In an attempt to solve complex issues such as how legal reasoning and argumentation coul ...
Automated Reasoning for Mizar: Artificial Intelligence through Knowledge Exchange
Automated Reasoning for Mizar: Artificial Intelligence through Knowledge Exchange

... axioms, make little use of previously accumulated knowledge, and do not attempt to further accumulate and organize the body of knowledge. • The benefits for the field of general Artificial Intelligence. These benefits are perhaps the least mentioned ones3 , however to the author they appear to be th ...
Symmetry Reduction for SAT Representations of Transition Systems
Symmetry Reduction for SAT Representations of Transition Systems

... Our idea is to not consider equivalence classes of states directly, but instead equivalence classes of transition sequences. Expressing a lexicographic ordering on the transition sequences is much easier than representing the computation of canonical elements of equivalence classes of states, and yi ...
PDF 2 of 2 - Massachusetts Institute of Technology
PDF 2 of 2 - Massachusetts Institute of Technology

... in which, for any particular assignment of the first n-1 elements in each list, there is a single possible assignment of the last one. In the brother-of relation, there could be many pairs with the same first item and a different second item, but in a function, if you have the same first item then y ...
Cognitive Systems
Cognitive Systems

... A brief history • Late 40’s Allan Touring: theory of computation • 1948 Claude Shannon: A Mathematical Theory of Communication • 1948 Norbert Wiener: Cybernetics - Control and Communication in the Animal and the Machine • 1950 The Touring test • 1951 Marvin Minsky’s analog neural network • 1956 Dar ...
Chap1&2
Chap1&2

... – 1957, Skinner (American psychologist, behaviorist, and social philosopher) studied behaviorist approach to language learning ...
Toward a truly personal computer
Toward a truly personal computer

... Copyright  1997 ACM, Association for Computing The files on this disk or server have been provided by ACM. Copyright and all rights therein are maintained by ACM. It is understood that all persons copying this information will adhere to the terms and constraints invoked by ACM’s copyright. These wo ...
Neural Machines for Music Recognition
Neural Machines for Music Recognition

... The outside world is perceived by human beings through the senses. In the outside world all sorts of processes are going on that determine how the world is shaped. These processes generate patterns that are picked up by the senses to provide us with information about the state of the world. For inst ...
Argumentation Theory in the Field: An Empirical Study of
Argumentation Theory in the Field: An Empirical Study of

... 22% of the deliberants used at least 2 conflicting arguments, i.e, one attacks the other. From a purely logical point of view, the use of conflicting arguments is very grating. Yet, we know that some people try to portray themselves as balanced and unbiased, and as such use contradictory arguments t ...
Curriculum vitaeWEB_Feb2015 - Técnico Lisboa
Curriculum vitaeWEB_Feb2015 - Técnico Lisboa

... Systems/Intelligent Control (4th/5th year graduate courses in Mechanical Engineering and Information Systems and Computer Engineering, respectively). Evaluated by the students, with scores regularly high, average rating of 4.55 (on the scale of 1 to 5). November 2002 - November 2005 Junior Researche ...
Fuzzy Membership, Possibility, Probability and Negation in Biometrics
Fuzzy Membership, Possibility, Probability and Negation in Biometrics

... pair is a genuine one and vice versa. Unfortunately, the field of iris recognition is full of counter-examples to this ideal situation, some of them as old as the domain of iris recognition itself [3], [4] and others, very recent indeed [6]-[10], [24], [25], some of them in more direct connection wi ...
Intentional Embodied Agents
Intentional Embodied Agents

artificial intelligence (luger, 6th, 2008)
artificial intelligence (luger, 6th, 2008)

... propose a Bayesian based constructivist rapprochement. In this sixth edition, we touch on all these levels in the presenting the AI enterprise. The second commitment we made in earlier editions was to the central position of advanced representational formalisms and search techniques in AI methodolog ...
Publication : An introduction to Soar as an agent architecture
Publication : An introduction to Soar as an agent architecture

... More practically, from an implementation point-of-view, an architecture provides the foundation for significant reuse from one application to another. The architecture itself is reused, and, at least theoretically, any relevant encodings of knowledge in former applications can also be reused. In pra ...
Associative Algorithms for Computational Creativity
Associative Algorithms for Computational Creativity

... computers do things that at least appear to be creative? (3) Can a computer appear to recognize creativity? (4) Can computers themselves ever really be creative (as opposed to merely producing apparently creative performance whose originality is wholly due to the human programmer)? To be clear, this ...
Distributed Resolution for Expressive Ontology Networks
Distributed Resolution for Expressive Ontology Networks

Artificial Intelligence (AI) Machine Learning and AI Pattern Recognition
Artificial Intelligence (AI) Machine Learning and AI Pattern Recognition

... What is Artificial Intelligence? by John McCarthy. http://www-formal.stanford.edu/jmc/whatisai/ “After WWII, a number of people independently started to work on intelligent machines. The English mathematician Alan Turing may have been the first. He gave a lecture on it in 1947. He also may have been ...
Mario Alberto Garcia Espinosa
Mario Alberto Garcia Espinosa

... Information Security (course developed); COSC 5376 Network Security (course developed); COSC 5377 Wireless Security (course developed); COSC 5378 Survivable Systems (course developed); COSC 5379 Advanced Information Assurance (course developed). COSC 5590 Selected Topics: Wireless Security(course de ...
A Knowledge-Based Approach to Lexical Analogy
A Knowledge-Based Approach to Lexical Analogy

Brief Survey on Computational Solutions for Bayesian Inference
Brief Survey on Computational Solutions for Bayesian Inference

... The research team led by Professor Jorge Dias at the Institute of Systems and Robotics (University of Coimbra) have presented recent work on Bayesian inference exploiting datalevel parallelism. In particular, Duarte et al. [53] presented proof-of-concept work on a general-purpose “Bayesian Machine” ...
Planning Algorithms for Interactive Storytelling
Planning Algorithms for Interactive Storytelling

... algorithm will privilege the actions with lower costs. In previous work on an IS application we successfully explored actions with different costs [Barros and Musse 2005], and we believe that this subject deserves further study. Hence, a planning algorithm that can support actions with costs provide ...
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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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