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Where has Computational Intelligence got to (in Canada)?
Where has Computational Intelligence got to (in Canada)?

... “symbol system” except that logic usually provides a formal semantics (i.e., a theory of how the meaning of expressions is composed from the meanings of its parts) and a system of inference (at least for deductive inference, if not for inductive, abductive and practical reasoning). Nothing like that ...
CPSC 171 Artificial Intelligence Read Chapter 14
CPSC 171 Artificial Intelligence Read Chapter 14

... “All men are mortal” “Therefore Socrates is mortal” Logical systems developed for rational deduction and inference  syntax  semantics Problems  Not all intelligent behavior is mediated by logical deliberation  Big difference in solving problems “in theory” and in practice ...
Knowledge Representation
Knowledge Representation

...  J. Teresko. Information Rich, Knowledge Poor? Data warehouses transform information into ...
Propositional Calculus - Syntax
Propositional Calculus - Syntax

... The operators have different levels of precedence with negation binding more tightly, and exclusive or least tightly (in the order given on a previous slide). We only use parentheses to change the normal order ...
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Cognitive Science News 14,

... COGNITIVE ...
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... joachim.baumeister@denkbares.com ...
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Artificial Intelligence

... •  Annual prize awarded to the most human computer –  $2000 and Gold Medal ...
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... Key events: AI adulthood (barely) • Many commercial expert systems introduced, especially in the 1970s and 1980s • Fuzzy logic and neural networks used in controllers, especially in Japan and Europe • Recent developments and areas of great interest include: – Bayesian reasoning and Bayes nets – Ont ...
AI & ES PowerPoint Handouts
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... Overview of Expert Systems Limitations • Not widely used or tested. • Limited to relatively narrow problems. • Cannot readily deal with “mixed” knowledge. • Possibility of error. • Cannot refine own knowledge base. • Difficult to maintain. • May have high development costs. • Raise legal and ethica ...
A Sparse Texture Representation Using Affine
A Sparse Texture Representation Using Affine

... • Generality: goes beyond explicit reasoning, and even human cognition altogether • Practicality: can be adapted to many real-world problems • Amenable to good scientific and engineering methodology • Avoids philosophy and psychology ...
- RehanCodes
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... successfully in English (or some other human language) Knowledge representation to store information provided before or during the interrogation;  Automated reasoning to use the stored information to answer questions and to draw new conclusions  Machine learning to adapt to new circumstances and ...
511 - Data, Information, Knowledge and Processing
511 - Data, Information, Knowledge and Processing

... is made up of a set of rules analyses information about a specific type of problem. trys to solve a problem in the same way as a human expert ...
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Knowledge Representation in Artificial Intelligence using

... The research in AI is divided in to two categories Knowledge representation and general. For making the computer or Machine as intelligent as human being we require two things Knowledge representation and inference mechanism. Development of an AI system is a crucial task because some time we have in ...
slides - WSU EECS
slides - WSU EECS

... Aristotle: what are correct arguments/thought processes? Several Greek schools developed various forms of logic: notation and rules of derivation for thoughts; may or may not have proceeded to the idea of mechanization Direct line through mathematics and philosophy to modern AI ...
chapter - FSU Computer Courses for Non
chapter - FSU Computer Courses for Non

... labored years to codify facts such as "Once people die, they stop buying things." He uses a form of symbolic logic called "predicate calculus" to classify and show the properties of information in a standard way. Now, 19 years later, with over 600 person-years and $60 million invested, the Cyc knowl ...
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... and expert systems are major branches of that. The other is to use a computer's artificial intelligence to understand how humans think. In a humanoid way. If you test your programs not merely by what they can accomplish, but how they accomplish it, they you're really doing cognitive science; you're ...
Managing Knowledge for the Digital Firm
Managing Knowledge for the Digital Firm

... see if it's raining. If it is, then you grab your umbrella. If it's not raining, then you don't. There you have it: a rule base. • Knowledge frames "represent knowledge by organizing information into chunks of interrelated characteristics." Your knowledge frame would be comprised of the fact that wh ...
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... occur in people, many animals and some machines. • When did it all start? ...
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... • AI discovers computational complexity – Early programs worked by representing the basic facts and trying out a series of steps to solve the problem which was only tractable within micro worlds; NP-completeness showed that scaling up to larger problems was not always viable ...
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... Often there is no direct way to find a solution to some problem. However, you do know how to generate possibilities. For example, in solving a puzzle you might know all the possible moves, but not the sequence that would lead to a solution. When working out how to get somewhere you might know all th ...
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... Artificial Intelligence in the form of expert systems and neural networks have applications in every field of human endeavor. They combine precision and computational power with pure logic, to solve problems and reduce error in operation. Already, robot expert systems are taking over many jobs in in ...
AI_chapter1_3
AI_chapter1_3

... "The study of the computations that make it possible to perceive, reason, and act" (Winston, 1992) "The art of creating machines that perform functions that require intelligence when performed by people" (Kurzweil, 1990) ...
CS 904: Natural Language Processing
CS 904: Natural Language Processing

... image processing and vision robotics game playing speech recognition natural language understanding etc. ...
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Knowledge representation and reasoning

Knowledge representation and reasoning (KR) is the field of artificial intelligence (AI) dedicated to representing information about the world in a form that a computer system can utilize to solve complex tasks such as diagnosing a medical condition or having a dialog in a natural language. Knowledge representation incorporates findings from psychology about how humans solve problems and represent knowledge in order to design formalisms that will make complex systems easier to design and build. Knowledge representation and reasoning also incorporates findings from logic to automate various kinds of reasoning, such as the application of rules or the relations of sets and subsets.Examples of knowledge representation formalisms include semantic nets, systems architecture, Frames, Rules, and ontologies. Examples of automated reasoning engines include inference engines, theorem provers, and classifiers.
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