Week 1: An Overview of Artificial Intelligence
Respond to the Discussion Forum prompt on “Getting to each other (Optional): AI Gold Standards” and post some or all of your responses to that prompt (which is repeated here). Attempt to link your thoughts to concepts presented in Chapters 1 and 2 of the textbook.
Discussion Forum prompt on “Getting to each other (Optional): AI Gold Standards”
Watch this analysis of the “The Catch” by Willie Mays, as well as great fielding by other baseball players. I’ve chosen this athletic event and analysis because Willie Mays was a childhood hero of mine. Optionally, you can choose an analysis of another athletic human feat that can be compared to robotic and AI capabilities, and post on it instead.
Willie Mays Made “The Catch,” but How Great Was It? | Baseball Bits https://www.youtube.com/watch?v=htZNlCZ6uqE
Based on your prior knowledge, reading and viewing of various media, any additional research, posts of other students, and your instincts/biases/intuitions address one or more of the following questions about physical and intellectual capacities of natural and artificial systems.
- How long do you think it will be before a robot can perform something comparable to “The Catch”?
- What capabilities of a robot would be most important in accomplishing The Catch, and how far along are robots towards mastery on those individual or integrated capabilities?
- What aspects of the analysis are particularly notable to you? Where and how do the commentator’s observations, research, and hypotheses indicate insight or prior knowledge on the commentator’s part?
- Has the commentator left anything notable out of the analysis?
Week 2: Planning a Road Trip
Plan a road trip from any two locations that you wish, with multiple intervening overnight stops between the start location and the ultimate destination. Describe the road trip in your post, together with the criteria that you used to design and decide upon the route. How did any tools such as map-searching applications help this planning? Where you can, comment on how your strategies for route design relate to concepts and algorithms in the textbook, lectures, or other materials in the course.
Week 4: Additional Search and Propositional Inference
1. Modify utility values at leaves of the game tree of the “More Efficient Game Search” video lecture and hand simulate Minimax search with Alpha-Beta pruning on your modified trees. Alternatively, seek a modification that minimizes the number of pruned nodes/states and seek a modification that maximizes the number of pruned nodes/states.
2. Modify the constraint graph from the “Generalized Arc Consistency” video by changing binary constraints and rerunning the GAC algorithm on those modified graphs. You may choose to remove some constraints entirely and add brand new constraint arcs.
1. Start with the statement at the bottom of page 226 of Russell and Norvig (i.e., B1,1 (P1,2 ⋁ P2,1) and convert it to CNF without referencing the book’s solution on the facing page. Check your solution against the book’s.
2. Exercise 4 of Russell and Norvig’s online exercises for Chapter 7 “Logical Agents” at https://aimacode.github.io/aima-exercises/knowledge-logic-exercises/
3. Exercise 3, parts (c) and (d); and exercise 4, parts (a) and (c), from Poole and Mackworth’s Propositions and Inference exercises at http://artint.info/2e/html/ArtInt2e.Ch5.S11.html.
Week 5: Reasoning with Uncertainty
1. Exercise 1 from Poole and Mackworth’s “Reasoning with Uncertainty” exercises at http://artint.info/2e/html/ArtInt2e.Ch8.S9.html .
2. Exercises 1-4, 8, 21, 25 from Russell and Norvig’s online exercises for Chapter 12 “Quantifying Uncertainty” at https://aimacode.github.io/aima-exercises/probability-exercises/ (note that the page indicates Chapter 13 because that was the case on a previous edition – wherever you see a reference to Chapter 13, replace it with 12)
3. Exercises 4 and 5 from Poole and Mackworth’s “Reasoning with Uncertainty” exercises at http://artint.info/2e/html/ArtInt2e.Ch8.S9.html.
4. Exercise 6 Russell and Norvig’s online exercises for Chapter 12 (exercise appears misplaced in wrong set of exercises https://aimacode.github.io/aima-exercises/decision-theory-exercises/. In part 3 there should be an ‘=’ between the two probabilities.
5. Construct two Bayesian networks of approximately six binary-valued nodes each that differ from any of those in the texts and lecture, and compute selected full-joint, partial-joint, and conditional probabilities under the following conditions: P(X|Y) where Y are all ancestors of X; P(Y|X) where Y are all ancestors of X; and P(X|Y) where X and Y are not ancestrally related.