Podcast
Questions and Answers
Which of the following is NOT a key concept associated with Artificial Intelligence (AI)?
Which of the following is NOT a key concept associated with Artificial Intelligence (AI)?
The definition of AI as "The study of how to make computers do things at which, at the moment, people are better" was proposed by:
The definition of AI as "The study of how to make computers do things at which, at the moment, people are better" was proposed by:
Which of the following is NOT a field or term closely related to Artificial Intelligence (AI) and Machine Learning (ML)?
Which of the following is NOT a field or term closely related to Artificial Intelligence (AI) and Machine Learning (ML)?
What is the primary goal of Machine Learning (ML) algorithms?
What is the primary goal of Machine Learning (ML) algorithms?
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Which of the following best describes the term "Supervised Learning" in the context of Machine Learning?
Which of the following best describes the term "Supervised Learning" in the context of Machine Learning?
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Which of the following best represents the concept of "Knowledge Representation" in the context of Artificial Intelligence?
Which of the following best represents the concept of "Knowledge Representation" in the context of Artificial Intelligence?
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The term "Expert Systems" in the context of Artificial Intelligence refers to:
The term "Expert Systems" in the context of Artificial Intelligence refers to:
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Which of the following is NOT a characteristic of Artificial Intelligence (AI) systems, according to the definitions provided?
Which of the following is NOT a characteristic of Artificial Intelligence (AI) systems, according to the definitions provided?
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The definition of AI as "Machines that behave as though they were intelligent" was proposed by:
The definition of AI as "Machines that behave as though they were intelligent" was proposed by:
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Which of the following best represents the concept of "Logic" in the context of Artificial Intelligence?
Which of the following best represents the concept of "Logic" in the context of Artificial Intelligence?
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Study Notes
Course Overview
- BMIN 520-401 course covers topics in Artificial Intelligence (AI)
Course Topics
Module 2: Logic
- Covers Propositional Logic (Representation and Reasoning)
- Covers First Order Predicate Logic (Representation and Reasoning)
Module 3: Other Knowledge Representation
- Covers Semantic Networks
- Covers Frames
- Covers Knowledge Organization Systems and Ontologies
- Covers Semantic Webs and Trees
Module 4: Essentials of Expert Systems
- Covers Rules and Introduction to Expert Systems
- Covers Rule-Based Systems
- Covers Journal Club-Style Paper Presentations
- Covers Building an Expert System and PyKE
- Covers Probability and Introduction to Uncertainty
- Covers Biomedical Expert Systems
Module 5: Search
- Covers Intelligent Agents and Introduction to Search
- Covers Uninformed Search and Heuristic Search
- Covers Local and Population-based Search
Module 6: Uncertainty
- Covers Entropy and Information Theory
- Covers Bayesian Networks
- Covers State Machines and Dynamic Models
- Covers Labeled and Unlabeled Data
- Covers Unsupervised Learning
Artificial Intelligence
- AI is concerned with tasks that require complex and sophisticated reasoning processes and knowledge
- Examples of AI tasks: recognizing a face, interpreting text
- The promise of AI: Automation, Scale, Discovery & Innovation
Goals of AI
- Automation: speed, efficiency, and reduction of manual human effort
- Scale: Performing tasks at a scale that most/all humans cannot achieve
- Discovery & Innovation: Integrating information to find novel patterns, design, and strategies
Cognitive Computers
- Simulate human thought processes in a computerized model
- Made with algorithms
- Knowledgeable ONLY about what is taught
- Control ONLY what we give them to control
- Can continue to learn more – given data/environmental sensors
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Description
Review key topics from the syllabus of BMIN 520-401 at the University of Pennsylvania, covering Logic (Propositional and First Order Predicate), Knowledge Representation (Semantic Networks, Frames, Ontologies), and Semantic Webs. Dive into the course content with this comprehensive review.
