
Copyright Information: Copyright © Alan Mackworth, 2013
Lecture Description
This video lecture, part of the series Introduction to Artificial Intelligence with Alan Mackworth by Prof. Alan Mackworth, does not currently have a detailed description and video lecture title. If you have watched this lecture and know what it is about, particularly what Computer Science topics are discussed, please help us by commenting on this video with your suggested description and title. Many thanks from,
- The CosmoLearning Team
- The CosmoLearning Team
Course Index
- Intro 1: What is Artificial Intelligence?
- Intro 2: Representational Dimensions
- Intro 3: Applications of AI
- Search 1: Representation & Search Framework
- Search 2: BFS and DFS
- Search 3: Search with Costs & Heuristic Search
- Search 4: Heuristic Search: A*
- Search 5: A* Optimality, Cycle Checking
- Search 6: Iterative Deepening (IDS) and IDA*
- Search 7: Multiple Path Pruning, IDS and IDA*
- CSP 1: Branch & Bound, CSP: Intro
- CSP 2: Solving CSP Using Search
- CSP 3: Arc Consistency
- CSP 4: GAC Algorithm and Domain Splitting for CSPs
- CSP 5: Local Search
- CSP 6: Stochastic Local Search
- CSP 7: Stochastic Local Search Algorithms
- Planning 1: Representation
- Planning 2: Forward Planning and CSP Planning
- Planning 3: CSP Planning Wrap Up
- Logic 1: Intro & Propositional Definite Clause Logic
- Logic 2: Proof Procedures, Soundness and Completeness
- Logic 3: Bottom-up and Top-down Proof Procedures
- Logic 4: Top-Down Procedure, Datalog and Big Picture
- Uncertainty 1: Probability Theory: Intro
- Uncertainty 2: Conditional Probability, Bayes Rule, Chain Rule
- Uncertainty 3: Independence
- Uncertainty 4: Bayesian Networks Intro
- Uncertainty 5: Independence and Inference
- Uncertainty 6: Variable Elimination for Bayes Nets
- Decision Theory 1: Uncertainty Wrap-Up, Single Decisions
- Decision Theory 2: Single and Sequential Decisions
- Decision Theory 3: Optimal Policies for Sequential Decisions
- Perspectives and Final Review
Course Description
This course provides an introduction to the field of artificial intelligence. The major topics covered will include reasoning and representation, search, constraint satisfaction problems, planning, logic, reasoning under uncertainty, and planning under uncertainty.
Visit the official website for more lecture notes, full assignments with solutions, and more information on the course and Prof. Mackworth's research: http://www.cs.ubc.ca/~mack/CS322/
This course comes accompanied with a textbook written by Alan Mackworth himself, and David Poole from UBC: http://artint.info/
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