Complexity

Complexity is hard to understand.

Many of the greatest board games have a few rules that make for a "easy to learn, lifetime to master" label. Go, Othello, Chess, and Checkers are just a few examples of completely open-information, deterministic games. I'll focus on the Game of Go, since I'm most familiar with it.

In Go, complexity raises as the game progresses, whereas, in Chess complexity decreases as pieces are taken from the board. Checkers also decreases vastly in complexity as you play it, and as pieces are captured.

So, I've wondered for a while, how to make a very complex game with a few rules. Today, I had to slap myself, as I forgot how important recursion is. The Fibonacci Numbers come from two starting pieces, and one rule. Yet they are infinite, and describe many phenomena found in nature, like sunflower petals.

The Fibonacci numbers, however, are not a game.

Likewise, other infinite mathematical constructs, such as real numbers, can be generated by a simple recursive procedure.

In games, this boils down to a kind of simple explanation. The result of one round has to be important in figuring out what to do the next round.

In counting, as you count, "1,2,3,4..." you're really just saying:

n = 1;

while (true)

{

n = n+1

}

So you need the last "n" to get to the next "n".

In Go, recursion is found as you play.... you always add a piece to the board, so the last number of pieces go up. But there are many complex other ways that recursion subtly comes into play.

As you decide whether a piece is captured, you must look at all of the other pieces it is attached to to see if they are surrounded. This is a recursive question, as my friend Patrick can attest. He decided to program this in Flash and found that it was not as simple as one would think.

Questions of recursion are not evident in Chess' capture rules, which simply state that two pieces cannot occupy the same space at the same time. The status of the king is not important when asking whether a pawn can be captured.

This still does not answer how a game designer can, for instance, find out which 4 or 5 rules produces a fun, and complex system. But for a given set of rules, perhaps we can ask, "how does this lead to recursion."

Lost Bartle Types

Many of you will have heard of the 4 Bartle Types of MUD players.

1. Explorer

2. Socializer

3. Achiever

4. Killer

These types are often overheard among game designers applied to many games beyond muds. Socializers, for instance, may get joy out of a game like Animal Crossing, even though the socialization occurs purely with computer controlled AI.

Either way, I would like to propose a 5th type:

5. Organizer

Some people would say that this is a form of Achiever, but I would argue that it's quite the opposite. True Achievers, I would argue, aim to accumlate wealth, xp, gear, achievements, to gain some sort of "currency", which can simplistically be described as a number that goes up.

One of the basic fundamentals of games is "Do thing, number goes up". This is the mojo behind things as old school as high score charts.

Organizers, on the other hand, gain satisfaction from, many times, SUBTRACTION.

Free Cell is the most intriguing example I can find. You start with an exposed jumbled mess of cards, and aim to finish at 4 neatly organized piles.

Perhaps this is truly a part of Achievement, perhaps not. The point is, classic game design focuses much more heavily on Addition than Subtraction.

Another case that seems to not fit into classic Achievement models is found in games like Sim City. Having a city with a good road systems or happy citizens may be of higher focus than simply growing to the highest population. Many times in Sim City I would elect to use all "green" energy (wind and hydroelectric power) rather than burning coal. This makes little sense from the lens of the 4 Bartle types.

I look forward to hearing thoughts.