Explore Simple Game Algorithms with Color Walk: Part 5

We're continuing to look at different game algorithms using the simple game Color Walk as a sandbox for exploration and discovery. The last post covered our first foray into a non-trivial algorithm, namely the greedy algorithm. We found that using the strategy of grabbing the most blocks from the board on each move was a reasonable thing to try, and it outperformed all the previous trivial algorithms. Then we extended the greedy algorithm to look ahead one move and found that it performed even better. Now we're going to extend the greedy algorithm to look ahead arbitrarily far and see how far we can actually look before the run time of the algorithm becomes prohibitive. In this process we should be able to find a way to improve the current data structure of the board to make searching more efficient and allow the algorithm to search more moves ahead as a result.

Explore Simple Game Algorithms with Color Walk: Part 4

In this series we are taking a look at different game algorithms using the simple game Color Walk as a sandbox for exploration and discovery. The last post showed how to add multiple algorithms and select between them, as well as exploring a random choice algorithm and an enhanced way to skip useless choices for both round-robin and random choice. This post will get into our first non-trivial algorithm, the greedy algorithm. Greedy algorithms don't care too much about the future. They will look at the choices immediately in front of them and try to pick the choice that will get them the most stuff right away. That's why they're called greedy, you see? In this case, the greedy algorithm will pick the color that will remove the most blocks on the next turn. Let's see how it stacks up to the trivial algorithms.

Explore Simple Game Algorithms with Color Walk: Part 3

In this series we are taking a look at different game algorithms using the simple game Color Walk as a sandbox for exploration and discovery. The last post showed how to implement one of the simplest algorithms I could think of, round-robin, and how to develop some tooling around the game so that we can quickly run through multiple iterations in a batch mode and see statistics on the run. This post will start exploring some more algorithms, and we'll start needing to think about how to improve the algorithms so they aren't so naive.

Explore Simple Game Algorithms with Color Walk: Part 2

In this series we are taking a look at different game algorithms using the simple game Color Walk as a sandbox for exploration and discovery. The last post was an introduction that described what Color Walk is, explained how to get it running on your own setup, and presented some brainstorming of possible algorithms to explore. This post will start digging into the simplest of those algorithms: round-robin, but first, we need to build up some tooling around the Color Walk JavaScript code to make it easier to test out our algorithms and benchmark their performance. We'll use the round-robin algorithm as a vehicle to help develop this tooling, so we have something to play with while getting the benchmark tooling up and running.

Explore Simple Game Algorithms with Color Walk: Part 1

A few years ago, Jennifer Dewalt did a project where she created 180 websites in 180 days, one every day for half a year, to learn how to program. These "websites" were actually web pages within one website, but the plan and the execution were still quite amazing. I watched on and off as she created page after page, learning all about web development in the process. One page in particular caught my interest: the simple game called Color Walk.

In this game there's a 20x30 grid of colored blocks in five different colors. The top left block is blank, and there are five colored buttons to choose from. Click a button, and the blank space will expand by removing the adjacent colored blocks corresponding to the button clicked. The goal is to clear the board in as few clicks as possible.

Color Walk by Jennifer Dewalt

What Can One Do in a Year?

One year. Three hundred sixty-five days. Eight thousand seven hundred sixty hours. Seems like a lot of time, right? Where does it go, and what do we do with it all? If you're like me, you might spend the majority of that time sleeping, working, spending time with family and friends, doing chores, and eating, in roughly that order of time consumption. When all is said and done, I have about two hours a day of leisure time that I can do with as I please, although not every day. Maybe 300 days out of the year, let's say, I can do self-driven activities.

A Barely Adequate Guide to the Google Blogger API using Ruby

For some time now, I've been wanting to do some things with this blog that are just too tedious to do by hand. For instance, I'd like to download all posts with pictures to have a local copy, you know, just in case. Google leaves a bit to be desired in this regard with its backup feature. I would also like to get a word count of all of the posts I've written, just because I'm curious. These things would be done best with an API, so that's what this post is going to explore.