'Semantic net' presentation slideshows

KNOWLEDGE REPRESENTATION ???

KNOWLEDGE REPRESENTATION ???. Knowledge Representation Methods. Declarative Methods --knowledge is knowing WHAT Logical Approach Predicate Calculus Nonstandard Logics Fuzzy Logic Non-Logical Approach Semantic Net Frame (procedural features) Conceptual Dependency.

1.04k views • 84 slides

KNOWLEDGE REPRESENTATION ???

KNOWLEDGE REPRESENTATION ???. Knowledge Representation Methods. Declarative Methods --knowledge is knowing WHAT Logical Approach Predicate Calculus Nonstandard Logics Fuzzy Logic Non-Logical Approach Semantic Net Frame (procedural features) Conceptual Dependency.

1.01k views • 84 slides

CSNB234 ARTIFICIAL INTELLIGENCE

CSNB234 ARTIFICIAL INTELLIGENCE. Chapter 6 Knowledge Representation. (Chapter 7, pp. 223-258, Textbook) (Chapter 5, pp. 167-197, Ref. #1). Instructor: Alicia Tang Y. C. Knowledge Representation. Knowledge representation is certainly one of the most important topics

771 views • 55 slides

Chapter 5 Knowledge Representation

Chapter 5 Knowledge Representation. Xiu-jun GONG (Ph. D) School of Computer Science and Technology, Tianjin University gongxj@tju.edu.cn http:// cs.tju.edu.cn/faculties/gongxj/course/ai /. Outline. Knowledge & Knowledge representation Methodology for KR Logic Production System

596 views • 38 slides

Chapter 8 Knowledge Representation

Chapter 8 Knowledge Representation. Xiu-jun GONG (Ph. D) School of Computer Science and Technology, Tianjin University gongxj@tju.edu.cn http:// cs.tju.edu.cn/faculties/gongxj/course/ai /. Outline. Knowledge & Knowledge representation Methodology for KR Logic Production System

538 views • 37 slides

CSC 550: Introduction to Artificial Intelligence Fall 2008

CSC 550: Introduction to Artificial Intelligence Fall 2008. Knowledge representation associationist knowledge semantic nets, conceptual dependencies structured knowledge frames, scripts expert systems rule-based reasoning, heuristics reasoning with uncertainty. Knowledge representation.

439 views • 31 slides

K NOWLEDGE R EPRESENTATION

L ECTURE N OTES K NOWLEDGE R EPRESENTATION Khurshid Ahmad Professor of Artificial Intelligence Department of Computing University of Surrey. K NOWLEDGE R EPRESENTATION.

326 views • 31 slides

CS 8520: Artificial Intelligence

CS 8520: Artificial Intelligence. Knowledge Representation Paula Matuszek Fall, 2005. KR Introduction. General problem in Computer Science Solutions = Data Structures words arrays records list More specific problem in AI Solutions = knowledge structures lists trees

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Knowledge representation 22c:145 Artificial Intelligence The university of iowa

Knowledge representation 22c:145 Artificial Intelligence The university of iowa. Contrary to the beliefs of early workers in AI, experience has shown that Intelligent Systems cannot achieve anything useful unless they contain a large amount of real-world - probably domain-specific - knowledge.

419 views • 29 slides

Artificial Intelligence BCS-7

Artificial Intelligence BCS-7. By Riaz Ahmad COMSATS WAh Cantt. A Simple Quote.

346 views • 28 slides

Problem Independent Forward Chaining

Problem Independent Forward Chaining Forward chaining is a reasoning process that begins with the known facts and tries to work forward to find a successful goal.

405 views • 27 slides

Knowledge Representation

274 views • 27 slides

Announcements

419 views • 26 slides

Chapter 3 Knowledge Representation

Chapter 3 Knowledge Representation. Chapter 3 Contents. The need for a good representation Semantic nets Inheritance Frames Object oriented programming Search trees Combinatorial explosion Problem reduction. The Need for a Good Representation.

441 views • 25 slides

Concept Space Construction

Concept Space Construction. Todd Littell 27SEP06. Roadmap. Last Year: High quality concept space construction performed offline. First version of inference engine via graph operations. This Year: High quality concept space construction performed online.

419 views • 25 slides

Intelligent systems

445 views • 20 slides

Conceptual Graphs:

Conceptual Graphs:. Combing logic and semantic net. Motivations. Semantic networks & frame systems have trouble handling negation, the fact that something is not true disjunction quantification, the fact that something is true for all objects Conceptual graphs can handle them naturally.

465 views • 20 slides

Chapter 3 Knowledge Representation

Chapter 3 Knowledge Representation. Chapter 3 Contents. The need for a good representation Semantic nets Inheritance Frames Object oriented programming Search trees Combinatorial explosion Problem reduction. The Need for a Good Representation.

216 views • 20 slides

Web Passive Voice Tutor: an Intelligent Computer Assisted Language Learning System over the WWW

Web Passive Voice Tutor: an Intelligent Computer Assisted Language Learning System over the WWW. Maria Virvou & Victoria Tsiriga Department of Informatics, University of Piraeus, 80 Karaoli & Dimitriou St.,Piraeus 18534, Greece mvirvou@unipi.gr , vtsir@unipi.gr. Overview.

318 views • 12 slides

Convergence

Convergence. Chris Chapman Chairman Australian Communications and Media Authority CAMLA Seminar May 30 2011. Smart homes. Wall screens. Flex screens. Single terminal. Screenless displays. Super HD. Adaptive national regulation. Layered convergence regulator.

153 views • 2 slides