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Constraint propagation
Constraint propagation

... and managing it . The LENAT experiment: 15 years of work by 15 to 30 people, trying to model the common knowledge in the word !!!! Knowledge should be learned, not engineered. ...
AI and Cognitive Science Trajectories: Parallel but diverging paths? Ken Forbus Northwestern University
AI and Cognitive Science Trajectories: Parallel but diverging paths? Ken Forbus Northwestern University

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Course Syllabus - Dr. Randy Ribler
Course Syllabus - Dr. Randy Ribler

... artificial intelligence. Core topics include search, knowledge representation, and reasoning. Additional topics may include game theory, planning, understanding, natural language processing, machine learning, neural networks, genetic algorithms, expert systems, and real-time systems. Students develo ...
Artificial Intelligence
Artificial Intelligence

... human-like reasoning problems of the real world It may be noted that a conventional set contains its members with a value of membership equal to one and disregards other elements of the universal set, for they have zero membership. The most common operators applied to fuzzy sets are AND (minimum), O ...
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... – How can artifacts operate under their own control? – The artifacts adjust their actions • To do better for the environment over time • Based on an objective function and feedback from the environment ...
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... Science Approach 1. Systems that think like humans 2. Systems that act like humans Engineering Approach 1. Systems that think rationally 2. Systems that act rationally ...
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... • The idea of microworlds, i.e. a limited domain in which its problem requires intelligence to solve (famous microworlds – blocks world). ...
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Behaviour Based Knowledge Systems

... Aims to bridge the gap between behaviour and knowledge based systems.  Implications for understanding of emergence of cognitive intelligence  Also holds implications for the application of these methods in future systems. ...
人工智能 - Lu Jiaheng's homepage
人工智能 - Lu Jiaheng's homepage

... • Can sense certain aspects of their environment • Can change their environment • May “evolve” and acquire additional capabilities over time ...
Programming with C++ CT214
Programming with C++ CT214

... The study and design of machines that simulate the human mind to perform intelligent tasks. Borrow many ideas from psychology, neuroscience. Goal is to perform tasks the way a human might do them – which makes sense, since we do have models of human thought and problem solving. ...
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... the inputs produce a known set of outputs and conclusions. Computer learns the correct solution by example Address the problems in pattern classification, prediction and financial analysis, and control and ...
chapter 1 - Blog Bina Darma
chapter 1 - Blog Bina Darma

... 1960s ``cognitive revolution'': informationprocessing model replaced prevailing orthodoxy of behaviorism • Scientific theories of internal activities of the brain What level of abstraction? “Knowledge'' or “circuits”? Cognitive science: Predicting and testing behavior of human subjects (top-down) ...
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... The Dartmouth Conference ● The Dartmouth Conference took place in 1956 and was where the field of AI research was essentially founded and where the term Artificial Intelligence was coined. ● The people who attended became known as the leaders of artificial intelligence research for decades. ● They ...
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Artificial Intelligence

... the role of problem solving, vision, and language in understanding human intelligence from a computational perspective. Course Goals & Objectives: At the conclusion of this course, the successful (passing) students will have an understanding of the basic areas of artificial intelligence including pr ...
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... Integration of learning, reasoning, knowledge representation AI methods used in vision, language, data mining, etc ...
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An Effective Reasoning Algorithm for Question Answering System

... intelligent programs to perform the complicated task. In 1950s, Alan Turing presented a paper on Computing Machinery and Intelligence. The result of this paper was if a machine could pass certain test (known as Turing test) then it could be intelligent. In this paper Turing also considered a number ...
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... and pursuit, is thought to aim at some good ...
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Chapter 12: Artificial Intelligence and Modeling the Human State

... • Ideas, concepts, and relationships are more difficult for humans and machines. – Provoking bees causes them to sting. – What is a chair? ...
Artificial Intelligence presentation
Artificial Intelligence presentation

... Playing strategy games like chess against a computer , the knowledge base would contain strategies and moves, the player's moves would be used as the query, and the output would be the computer's “Expert” moves. ...
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... Dr. John D. Lowrance has been a member of SRI's Artificial Intelligence Center since 1980. He has led and participated in basic and applied research programs in perception, foundations for expert systems, uncertainty calculi for knowledge-based systems, knowledge-based planning methodologies, intell ...
THE PREDICATE
THE PREDICATE

... problem. Various tools and techniques have been devised for reasoning under incomplete data and knowledge. Some of these techniques employ: i) stochastic ii) fuzzy and iii) belief network models. In a stochastic reasoning model, the system can have transition from one given state to a number of stat ...
Workshop of Artificial Intelligence, Knowledge Discovery, and Fuzzy
Workshop of Artificial Intelligence, Knowledge Discovery, and Fuzzy

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AI from the Perspective of Cognitive Science
AI from the Perspective of Cognitive Science

... 4. Which program possesses more intelligence, Deep Blue (which beat Kasparov at chess) or General Problem Solver (GPS), which can solve simple “brain teaser” puzzles? Is it possible that they both work in the same way? 5. Which brand of AI is most relevant to Cognitive Science, Human AI or Alien AI? ...
Enhancing the Explanatory Power of Intelligent, Model
Enhancing the Explanatory Power of Intelligent, Model

... There is evidence that the organism that might be causing the infection is Staphylococcus coagpos (0.75) or Streptococcus ...
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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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