CSE 348 AI Game Programming Project 2: Pathfinding in Games

1. CSE 348 AI Game ProgrammingProject 2: Pathfinding in Games Due: Wednesday, February 29 Presented By: James Ahlum

2. The Framework • Pac-Man • Developed at UC Berkeley • Very well tested and documented • The instructions are excellent • We will focus on the search application of the framework

3. The Project • Search in Pac-Man • 5 Tasks • Depth-first Search • Breadth-first Search • A* Search • Transition Tables • A* Food Search • Find a path to eat all dots in the map as fast as possible • In-class competition to determine the winner

4. Setup • Download the Pac-Man Framework • You can get the zip file here or from the website • Unpack the zip file and store it in your desired location • Download Python • You want Python version 2.7.2 • Download it for various OS here • Select the desired installation location • Default for Windows is C:\Python27

5. Setup • Add Python to your Path • Windows: Computer > Properties > Advanced System Settings > Environment Variables (under Advanced Tab) • Find “Path” under System Variables > Edit it and *APPEND* C:\Python27 (or the directory where you installed Python) • Note: Do not replace the Path variable with C:\Python27, just append it using a semicolon • You should now be able to invoke the Python interpreter from the command line • Open a Command Prompt, switch to the “search” directory where you unpacked the zip file • Type “python pacman.py” to test your setup • It should open a GUI where you can use arrow keys to control Pac-Man

6. Development • Pseudocode for the algorithms will be presented in the next lecture • The only files you should need to edit are search.py and searchAgents.py • They are well commented and make it very clear where your code needs to go • An important note from the project website: • “Each algorithm is very similar. Algorithms for DFS, BFS, and A* differ only in the details of how the fringe is managed. So, concentrate on getting DFS right and the rest should be relatively straightforward.”

7. Development • I recommend using the data structures in util.py • Stack will be useful for depth-first search • Queue will be useful for breadth-first search • Priority Queue will be useful for A* • If you don’t know Python, learning it might take some time • The Pac-Man projects has a tutorial that goes over the basics and key things you’ll need to know for this project • There’s also an official Python tutorial and full documentation

8. Python • Data Structures • Lists: list = [2, ‘a’, “string”], list[0] == 2 • Tuples: pair = (1,2), pair[0] == 1 • Sets: mySet = set(), mySet.add(1), 1 in mySet == True • Dictionaries (associative arrays): f = {}, f[state] = 1.0, where state = (x,y) • Finding the length of a structure • len(“abc”) == 3, len(list) == 3 • Comments: • #single line comment, “””multi line comment”””

9. Debugging • Print to the command prompt • print “message” • for state in answer: print str(state) • Notice the str() method to print string representation • Log to a file • file = open(‘log.txt’, ‘w’) • file.write(‘log message \n’) • file.close()

10. Deliverables • Code • Email search.py and searchAgents.py to jfa306@lehigh.edu by midnight, Wednesday, February 29 • If you create any additional files (i.e. for your own data structures) or modify any existing files, also send those along with a detailed description of the additions/modifications • Presentation & Report • As explained in the project description, due Thursday, March 1

11. That’s All • Questions? • Email jfa306@lehigh.edu with CSE348 in the subject, CC munoz@cse.lehigh.edu