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... • Constraints can be handled in a deterministic way without loosing completeness. • Efficient constraint solving methods exist for the domain. • The computation domain can be used for more than one application. A number of computation domains have been identified which satisfy these conditions, and ...
The Role of Subjectivity in Intelligent Systems Communication and
The Role of Subjectivity in Intelligent Systems Communication and

... constrained by social grouping, material and symbolic resources as well as cognitive factors. ...
An analytic approach for obtaining maximal entropy OWA operator weights ∗ Robert Full´er
An analytic approach for obtaining maximal entropy OWA operator weights ∗ Robert Full´er

... Additionally, Fuller and Majlender (2001) used Lagrange multipliers on Yager’s OWA equation to derive a polynomial equation, which determines the optimal weighting vector under maximal entropy (ME-OWA operator). The proposed approach thus determines the optimal weighting vector under maximal entropy ...
Humour - CSE, IIT Bombay
Humour - CSE, IIT Bombay

... Dry humour is a form of humour which is narrated as if it is not a joke at all (i.e. narrated in a serious tone, perhaps.) ...
Intelligent Distributed Agent Based Architecture
Intelligent Distributed Agent Based Architecture

... The new approach to coordination was inspired by social networks, as observed in higher mammalian societies. Two social relationships were explored, namely kinship and trust. Coordination is achieved through team selection. Using characteristics of social networks, such as learning and the ability t ...
Synthetic Super Intelligence and the Transmutation of
Synthetic Super Intelligence and the Transmutation of

... Copyright ©2016 Wes Penre Productions. All rights reserved. This is an electronic e-book, free of charge, which can be downloaded, quoted from, and copied to be shared with other people, as long as nothing in this paper is altered or quoted out of context. Not for commercial use. Editing provided b ...
MATHEMATICAL LOGIC FOR APPLICATIONS
MATHEMATICAL LOGIC FOR APPLICATIONS

... Frege. Logic has been a device to research foundations of mathematics (based on results of Hilbert, Gödel, Church, Tarski), and main areas of Logic became full-fledged branches of Mathematics (model theory, proof theory, etc.). The elaboration of mathematical logic was an important part of the proc ...
The influence of robots on the human society
The influence of robots on the human society

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10. Fuzzy Reasoning - Computing Science

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... on the abstract level of inference operations was proposed and motivated by A. Tarski in [37]. The classical example of a deductive system is the inference system denoted by L0 = (L0 , Cn) which is based on classical propositional logic. Here L0 is the set of propositional formulas based on a set of ...
Chapter 02 Decisions and Processes: Value Driven Business
Chapter 02 Decisions and Processes: Value Driven Business

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Heuristics - UCLA Cognitive Systems Laboratory
Heuristics - UCLA Cognitive Systems Laboratory

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Monster Analogies - Semantic Scholar
Monster Analogies - Semantic Scholar

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Monster Analogies - Semantic Scholar

... which show that analogy need not be regarded as something having a single form, format, or semantics. Analogy clearly does depend on the human ability to create and use well-defined or analytic formats for laying out propositions that express or imply meanings and perceptions. Beyond this dependence ...
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... effect is an increased flexibility of the model class, which can indeed be useful and improve performance, especially if the original class is quite restricted. For example, fuzzy rule induction gets rid of restrictions to axis-parallel decision boundaries, which may improve classification accuracy ...
INSTITUTE OF ADVANCED LEGAL STUDIES SCHOOL OF
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... examined since the introduction of the first commercially available desktop computer. In the early 1950s Herbert Simon, Allen Newell and Cliff Shaw conducted experiments in writing programs to imitate human thought processes. The experiments resulted in a program called Logic Theorist, which consist ...
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... and testing search algorithms. Classical approaches to heuristic search and planning assume a deterministic model of sequential decision making in which a solution takes the form of a sequence of actions that transforms a start state into a goal state. The effectiveness of heuristic search for class ...
6.034 Artificial Intelligence. Copyright © 2004 by Massachusetts
6.034 Artificial Intelligence. Copyright © 2004 by Massachusetts

... skolemize, named after a logician called Thoralf Skolem. Imagine that you have a sentence that looks like: there exists an x such that P(x). The goal here is to somehow arrive at a representation that doesn't have any quantifiers in it. Now, if we only had one kind of quantifier in first-order logic ...
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... coalitions. For the development of the required algorithms, we combine a combinatorial algorithmic approach and concepts from operations research, with autonomous agents’ methods and distributed computing systems methods. The coalitions the agents form when using these algorithms are beneficial for ...
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Automated Theorem Proving in a First

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A reasoning model based on the production of acceptable arguments

... quantified with a degree in [0, 1]. In particular, it should be possible to assess the reason why a fact holds, in the form of arguments, and combine these arguments to evaluate the certainty. Indeed, the process of combination may be viewed as a kind of reasoning about the arguments in order to det ...
lesswrong.com
lesswrong.com

... network of arithmetical facts to cover common-sense truths. • Need Artificial Arithmetician that can understand natural language, so instead of being told that twenty-one plus sixteen equals thirty-seven, it can obtain knowledge by reading Web. • Need to develop General Arithmetician the same way Na ...
Adding Consciousness to Cognitive Architectures
Adding Consciousness to Cognitive Architectures

... 14.8 Abstract view of Production memory . . . . . . . . . . . . . 14.9 The Blocks-World . . . . . . . . . . . . . . . . . . . . . . . . 14.10Soar WM in the Blocks-World example. . . . . . . . . . . . 14.11Soar organisation . . . . . . . . . . . . . . . . . . . . . . . . 14.12Example of an ACT-r chun ...
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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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