SLOG Post #6 - Assignment 2

For this week's SLOG post, I'm going to reflect on Assignment 2. Overall, I think this project went quite well. I liked it a lot more than the first assignment because I found that the tasks were a lot more clearly defined, which made it less stressful on our end. The most difficult part for me was writing the minimax strategy. I spent a long time reading the instructions sheet and trying to wrap my head around it. I found that drawing out Trees was really helpful during the design process. It made it really easy for me to trace the function and understand what it needed to do.

Minimax

Early on, I made an important design decision for the implementation of minimax: I would use a recursive helper function, get_score, to find the score for every possible move at the current game state, and then use the Strategy class method suggest_move to (randomly) pick one of the moves that had the highest score. This allowed me to create a recursive function that only needed to keep track of score, but not move. I've included the Tree from the assignment sheet as an example:

Imagine that it is player A's turn (the computer) in a game of Subtract Square, the current number is 6. Once the computer asks for a move suggestion using minimax, the StrategyMinimax method suggest_move calls get_score on the game states that can be reached with the two possible valid moves that can be made at that point (subtract 1 and subtract 4). get_score would recurse down these two "subtrees" to find the score for player A at both of these game states. In this case, subtracting 4 would lead to a winning game state where A has a score of +1 (B:2), and subtracting 1 would also lead to a winning game state (B:5, +1 for A). Upon knowing the scores, suggest_move randomly returns one of the moves that leads to a game state with the highest score (in this case, they both have the same score, so it doesn't matter which is returned). suggest_move keeps track of which score is associated with each move by keeping two parallel lists, one with game states that can be reached from the current game state, and one with scores (produced by get_score) that are in the same order as the game states.

So that's how my minimax strategy worked. I read the post on Biron's SLOG (http://grandslog148.blogspot.ca/, Week 7 and Assignment 2), and I sympathize with his struggle to design minimax. This function was quite difficult for me, and it took much longer to figure out than anything I've had to do in other computer science projects.

Based on what the other students have done, and on what our profs have told us, I don't think my implementation is quite the same as the expected or "correct" implementation. However, I'm pretty confident that it works, and I have thoroughly tested it. I fear that I might lose some credit because, technically, it does not work exactly as their description of minimax does: the recursive part of the strategy does not keep track of the moves as it recurses: it only carries the score.

Python Style Checker

I was having some issues with the python style checker, pep8. I noticed that it would give me an error for having lines that were greater than 79 characters for some of my docstring examples that involved dictionaries. However, I couldn't think of a way to fix it, since condensing the dictionaries (ie fitting them on multiple lines) would cause the doctest to fail, and that was also something that I wanted to avoid. I will be sure to find a solution to this problem before I hand in Assignment 3.