Writing Halite.io bots can be adicting. The behavior of a bot can be tweaked in many ways and then watched using the Visualize option on the website. It doesn’t take long to have a number of different code paths depending on what is surrounding a particular square. By the time my original bot was working relativley well, the code had become pretty complex and a new starter package was available for clojure, so I decided to rewrite the bot in Clojure with the hope that it would be easier to build on. This is the first time that I have taken existing Java code that I have written and have rewritten it in clojure. It took longer than I expected.
Starter package differences
The biggest difference between the java starter package and the clojure starter package is that the java version calls a move method each time it finds an owned square while the clojure package builds a list of owned squares and then processes the whole list. I had already made that same change to the java version so that was not an issue. The issue that I ran into was that I had a lot of nested logic. I had an if statement checking for strength of zero so that square would not move. I treated squares on the frontier different from the squares that were surrounded by squares that I owned. I checked if it was possible for a square to overtake an adjacent square. I checked if one of the adjacent squares that I owned had enough strength to help to be able to overtake a square. When I tried to convert all this logic to clojure it looked horible.
Method size vs Function size
I don’t know that directly translated logic really was any worse in Clojure, but it sure felt worse. There doesn’t seem to be as much interest in smaller methods in Java as there is in other languages. In how much should global variables cost Ben Orenstein said there should be a tax of $3.00 on methods over 5 lines long. Looking for similar references for Java found mentions of hardly ever over 20 lines or 65 or more and less than 30. For some reason, the nested code in Java did not look as bad to me as it did in clojure.
By the second clojure version I had smaller methods and the code was getting a little easier to understand, but still had a lot of layers of checking if a rule applied and then applying that rule.
A bigger problem came with getting help from another square. A helper square had to be removed from the list of sites being processed which meant that a simple map or reduce no longer could be used to process the squares. These two issues were solved together with pie.
Young Agent K: We need pie. Agent J: What? Young Agent K: My grand daddy always said, if you got a problem that you can't solve, helps to get out of your head. Pie, it's good.
Who knew that cross country skiing is a valid substitute for pie. It may not be in most situations, but taking a ski break gave me a flash of insight that solved this code problem.
The complexity problem was solved by individual move functions that only return a move if the site meets the criteria.
The key is the lack of else conditions. Each individual move function is put into a list. A some function tries each function until it finds a move that applies.
The solution to the second problem of the helper sites can also be seen in these examples. The calculated move is being returned in a vector along with the rest of the sites yet to process. For the squares that require help, the move vector will have 2 entries and the list of remaining sites will have have the helper site removed. A recursive move function is called with the updated list of sites yet to be processed instead of mapping over a list.
The current bot looks only at what is right around the square being moved, but the whole game map is available for analysis. There might be a way to optimize the overall direction of attack by looking at the shape of the map.