CS 371 Introduction to Artificial Intelligence Homework #1

Due: Tuesday 9/5
1. Read R&N Ch.1. How would you define AI and why? What is its place in the context of Computer Science?
2. R&N Exercise 1.9 + 1.10
3. R&N Exercise 2.4
4. Uninformed Search: Consider the following graph where nodes are states, arcs are operators labeled with costs, A is the initial state, and G is the goal state:
5. In this exercise, you will give the order in which nodes are goal-tested according to different search strategies employing different ways of avoiding repeated states. List the order of node goal-testing until the goal G is tested or 18 nodes have been listed. Ties in node ordering are broken alphabetically by state label. The ways in which repeated states are avoided are as follows:

• "Generate all": Repeated states are not avoided; all nodes are generated.
• "No self-loop": Do not return to the state you just came from.
• "No cycles": Do not create paths with cycles in them.
• "No repeats": Do not generate any state that was ever generated before.

•

### No repeats

Uniform Cost

Depth-First

Depth-Limited
(limit=1)

Iterative Deepening

6. TripleCross Challenge #1 [Collaboration in pairs is permitted.] Program depth-first search for TripleCross. There are two separable parts to this project.  The first task is to code a TripleCross search state class.  (See David Barr's TripleCross page.)  The second task is to code DFS.  To aid you in this programming adventure, please take advantage of code of a similar nature which can be found in folders Queue and search in the class code repository.  There, you will find not only an implementation of breadth-first search for the tile-puzzle, but also abstract classes State, Operator, and Searcher which should be extended for your own implementations.  (The Queue class need not be used.)  Use a state search limit such that your code will terminate within 10 seconds.  Then experiment to see how scrambled the puzzle can be to reliably find a solution.  For instance, what percentage of the time will it find a solution 10, 15, or 20 random moves from the start state?  It's up to you decide what means to use to avoid infinite loops.  For instance, you could decided to add a an option to limit depth (thus creating depth-limited search) or go a bit further and implement iterative deepening (probably the most practical option).  Alternatively, you could implement one of the repeated-state avoidance methods above with varying memory costs.  Or you could do a combination of each    Submit code as directed on the class homepage, and submit a brief (< 1 page) description of your design and experimentation.  Most importantly, have fun with it!  (Note: If you enjoy this puzzle, a simpler version is available from Binary Arts as "Port to Port", available at Amazon, etc.)

(c) 2000 Todd Neller