Sessions

6. Search: Games, Minimax, and Alpha-Beta

4 years ago
Want create site? Find Free WordPress Themes and plugins.MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: ocw.mit.edu/6-034F10 Instructor: Patrick Winston In this lecture, we consider strategies for adversarial games such as chess. We discuss the minimax algorithm, and how alpha-beta pruning improves its efficiency. We then examine progressive deepening, which ensures that some […]

16. Learning: Support Vector Machines

4 years ago
Want create site? Find Free WordPress Themes and plugins.MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: ocw.mit.edu/6-034F10 Instructor: Patrick Winston In this lecture, we explore support vector machines in some mathematical detail. We use Lagrange multipliers to maximize the width of the street given certain constraints. If needed, we transform vectors into another […]

Mega-R4. Neural Nets

4 years ago
Want create site? Find Free WordPress Themes and plugins.MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: ocw.mit.edu/6-034F10 Instructor: Mark Seifter We begin by discussing neural net formulas, including the sigmoid and performance functions and their derivatives. We then work Problem 2 of Quiz 3, Fall 2008, which includes running one step of back […]

Mega-R6. Boosting

4 years ago
Want create site? Find Free WordPress Themes and plugins.MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: ocw.mit.edu/6-034F10 Instructor: Mark Seifter This mega-recitation covers the boosting problem from Quiz 4, Fall 2009. We determine which classifiers to use, then perform three rounds of boosting, adjusting the weights in each round. This gives us an […]

Mega-R1. Rule-Based Systems

4 years ago
Want create site? Find Free WordPress Themes and plugins.MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: ocw.mit.edu/6-034F10 Instructor: Mark Seifter In this mega-recitation, we cover Problem 1 from Quiz 1, Fall 2009. We begin with the rules and assertions, then spend most of our time on backward chaining and drawing the goal tree […]

5. Search: Optimal, Branch and Bound, A*

4 years ago
Want create site? Find Free WordPress Themes and plugins.MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: ocw.mit.edu/6-034F10 Instructor: Patrick Winston This lecture covers strategies for finding the shortest path. We discuss branch and bound, which can be refined by using an extended list or an admissible heuristic, or both (known as A*). We […]

17. Learning: Boosting

4 years ago
Want create site? Find Free WordPress Themes and plugins.MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: ocw.mit.edu/6-034F10 Instructor: Patrick Winston Can multiple weak classifiers be used to make a strong one? We examine the boosting algorithm, which adjusts the weight of each classifier, and work through the math. We end with how boosting […]

Mega-R3. Games, Minimax, Alpha-Beta

4 years ago
Want create site? Find Free WordPress Themes and plugins.MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: ocw.mit.edu/6-034F10 Instructor: Mark Seifter This mega-recitation covers Problem 1 from Quiz 2, Fall 2007. We start with a minimax search of the game tree, and then work an example using alpha-beta pruning. We also discuss static evaluation […]

15. Learning: Near Misses, Felicity Conditions

4 years ago
Want create site? Find Free WordPress Themes and plugins.MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: ocw.mit.edu/6-034F10 Instructor: Patrick Winston To determine whether three blocks form an arch, we use a model which evolves through examples and near misses; this is an example of one-shot learning. We also discuss other aspects of how […]

21. Probabilistic Inference I

4 years ago
Want create site? Find Free WordPress Themes and plugins.* Please note: Lecture 20, which focuses on the AI business, is not available. MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: ocw.mit.edu/6-034F10 Instructor: Patrick Winston We begin this lecture with basic probability concepts, and then discuss belief nets, which capture causal relationships between events […]

9. Constraints: Visual Object Recognition

4 years ago
Want create site? Find Free WordPress Themes and plugins.MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: ocw.mit.edu/6-034F10 Instructor: Patrick Winston We consider how object recognition has evolved over the past 30 years. In alignment theory, 2-D projections are used to determine whether an additional picture is of the same object. To recognize faces, […]

22. Probabilistic Inference II

4 years ago
Want create site? Find Free WordPress Themes and plugins.MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: ocw.mit.edu/6-034F10 Instructor: Patrick Winston We begin with a review of inference nets, then discuss how to use experimental data to develop a model, which can be used to perform simulations. If we have two competing models, we […]