'Semantic nets' presentation slideshows

Chapter 2: The Representation of Knowledge

Chapter 2: The Representation of Knowledge. Expert Systems: Principles and Programming, Fourth Edition. Objectives. Introduce the study of logic Learn the difference between formal logic and informal logic Learn the meaning of knowledge and how it can be represented Learn about semantic nets

639 views • 51 slides

Chapter 7: The Representation of Knowledge

Chapter 7: The Representation of Knowledge. Expert Systems: Principles and Programming, Fourth Edition. Objectives. Introduce the study of logic Learn the difference between formal logic and informal logic Learn the meaning of knowledge and how it can be represented Learn about semantic nets

628 views • 50 slides

machine learning

470 views • 34 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

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

480 views • 30 slides

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

Knowledge representation

Knowledge representation. Intelligence requires the ability to represent information about the world, and the ability to reason with the information. knowledge representation schemes logical: use formal logic to represent knowledge - PL, FOPL

281 views • 28 slides

Knowledge Representation

274 views • 27 slides

Data and Applications Security Developments and Directions

Data and Applications Security Developments and Directions. Dr. Bhavani Thuraisingham The University of Texas at Dallas Inference Problem - II September 2012. Outline. Security Constraint Processing Use of Conceptual Structures. Security Constraint Processing.

542 views • 26 slides

Announcements

420 views • 26 slides

Data and Applications Security Developments and Directions

Data and Applications Security Developments and Directions. Dr. Bhavani Thuraisingham The University of Texas at Dallas Lecture #8 Inference Problem - II February 8, 2006. Outline. Security Constraint Processing Use of Conceptual Structures. Security Constraint Processing.

354 views • 26 slides

Data and Applications Security Developments and Directions

Data and Applications Security Developments and Directions. Dr. Bhavani Thuraisingham The University of Texas at Dallas Lecture #12 Inference Problem - II September 24, 2010. Outline. Security Constraint Processing Use of Conceptual Structures. Security Constraint Processing.

267 views • 26 slides

Data and Applications Security Developments and Directions

Data and Applications Security Developments and Directions. Dr. Bhavani Thuraisingham The University of Texas at Dallas Lecture #8 Inference Problem - II February 8, 2006. Outline. Security Constraint Processing Use of Conceptual Structures. Security Constraint Processing.

264 views • 26 slides

CSC 550: Introduction to Artificial Intelligence Fall 2004

CSC 550: Introduction to Artificial Intelligence Fall 2004. Knowledge representation associationist knowledge semantic nets, conceptual dependencies structured knowledge frames, scripts alternative approaches. Knowledge representation. underlying thesis of GOFAI: Intelligence requires

262 views • 26 slides

Artificial Intelligence

Artificial Intelligence Artificial Intelligence Artificial intelligence (AI) is a broad field, and means different things to different people.

1.15k views • 23 slides

Semantic Nets [1]

Example 1 Represent the following sentences using a semantic net: (a) Tom is a cat. (b) Tom caught a bird. (c) Tom is owned by John. (d) Tom is ginger in colour. (e) Cats like cream. (f) The cat sat on the mat. (g) A cat is a mammal. (h) A bird is an animal.

229 views • 5 slides