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Why Large Decision Spaces are Boring

Genius removes complexity quote

Genius removes complexity quoteI played a friend’s prototype a couple of days ago. Interesting concept for a hint-giving semi-coop deduction game, sort of a cross between Dixit, Clue and Mastermind.

It didn’t work.

Now, don’t get me wrong. The idea was good, the mechanics were pretty solid, the graphics were gorgeous. The game should have worked, and yet it didn’t. It didn’t work because the graphics were gorgeous.

See, one aspect of the game was finding things in the images. And the images were interesting, complex images, full of life, mysterious objects, highlights, all that stuff that makes games nice to look at. But when it came to deciding on a thing in the image they were a disaster.

There simply was too much things to choose from. The decision space was too large.

Let’s take another game: Go. In Go you can place your stone (that’s like a pawn in Chess) in any of 19 x 19 places. That’s 361 distinct positions. And it’s way too many.

That’s why beginners often start playing Go on limited boards: 13×13, 11×11. I’ve even seen people playing a 9×9 board when demonstrating the game. That’s because the rules for Go are very simple – there are only 9 of them, including the ever popular rule #1: The Game Board begins empty. But when you get 361 spaces to place your stones, and you know nothing about weighing your positions, or tsumego (life-and-death) situations or any of the other emergent elements of Go, your only option is to place stones at random. You simply don’t know enough to make an informed choice.

And that’s boring.

Go gameThat’s why Go beginners are taught on smaller boards. Smaller boards mean smaller decision spaces, and smaller decision spaces means that players with limited experience and knowledge can still make informed decisions.

I’m not saying that smaller boards or smaller decision spaces act as equalizers between experienced and inexperienced players (they might – just look at Snakes and Ladders – but they don’t have to). I’m not even saying that a game is less challenging in a smaller decision space. What I am saying is that if the decision space is too large then the game is no fun to play.

Let’s say that I’ve got to choose one move from ten thousand possible moves, and let’s say that the moves are evenly distributed along an axis going from “bad” go “good”. There’s one move that will guarantee me victory, another that will guarantee me defeat, and a bunch of moves in the middle. Problem is, I don’t know which move is which. There are a few possible outcomes:

  1. I have no idea that there’s even an axis. To me all the moves are equally confusing. I play at random and not knowing what I’m doing I’ll get bored very fast (unless I’m a 3 year old, but that’s going into developmental psychology).
  2. I know that some moves are better than others but I don’t now which and I have no way to tell. Now I’m playing at random AND I know that I shouldn’t do that. This leads to frustration.
  3. I know that some moves are better and I’ve got an idea of which but I’m not able to weigh the particular move. So I know not to do the generally bad moves (like fighting a land war in Asia) but I have no idea if it’s better to attack Brunei or China. When it comes down to the particulars I’m still playing at random. This is more interesting than playing completely at random but still not very.
  4. I know that some moves are better and I have the ability to weigh moves against each other. Whoa, holy plays, Batman! This is the Grail, right? Not quite. This type of play leads to analysis paralysis, where players will sit and think, and think, and think, and think, and…

But let’s look at this from the opposite perspective, the perspective of a game with limited decision spaces. Let’s take Tic-Tac-Toe.

Tic-Tac-Toe has got a very limited decision space. 9 spaces in all, and decreasing fast. If you don’t know anything about Tic-Tac-Toe you still begin by playing at random. But very rapidly you get feedback: some moves are better than others. You’ve reached stage 2 above. Unless you’re a small, pre-operational (to use Piaget’s term) child you realize that playing in the center is better than playing in the corner which is better than playing in the middle of the sides. You can now play the game and will very soon reach the stage where the game is solved for you. You’ve outgrown Tic-Tac-Toe.

Yeah, it’s a silly example. Who wants to play a game that they can solve in 10 minutes flat? But the other end is just as bad: who wants to play a game that they can’t even begin to understand? It’s like being at a party where everyone else is laughing and you don’t get the joke.

Going back to our original premise, my friend’s game and the enormous graphical decision space. With that much decisions to make it was a chore to search through endless amounts of items in order to find one to either formulate a clue about or guess for. The decision space was too large, and the game became less fun.

Go gameSame with Go: the first time I tried playing it I played it on a 13×13 board (as suggested in the book I bought to go along with it) and I had no idea what I was doing. I kept putting down stones at random (just like my opponent, who was also fresh to Go) and I was bored. It wasn’t until I realized that there were ways to set up a kill (internal Go term, go read up about it) that I realized that the game had lots of potential to be fun.

Contrast this with a professional Go demo I saw at a gaming fair. The instructors showed the game on a 9×9 board, they introduced only some of the rules (a very quick “chain building game”, followed by an equally quick “killing game”) and then let players try the game with all the rules but in this very limited decision space. And lo and behold, people who’d never played Go enjoyed it immensely. They were able to very quickly go from not knowing what to do to seeing ways in which they could affect the game in their own favor. They had fun. And they kept learning very fast, meaning that they could be presented with an 11×11 board and a larger decision space in a matter of half an hour and then enjoy that.

This is why there are playable tutorials. This is why you don’t want to throw a newbie into the middle of a pro-deathmatch game. This is why you should strive to have emergent gameplay, or engine building, in your game. To present people with a limited decision space in which they can act in an informed way that will let them take command of the game instead of the game taking command of them. That will hook them on your game.

And once hooked, you can slowly increase the decision space, teaching them and expanding their action horizons as they play along.

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  • Luke Laurie

    Great piece! I firmly believe that a core aspect of how a game should be designed is considering the decision space and how it may change throughout the game. Well done.

    • Filip Wiltgren

      Thanks! I’ve noticed that too, and the most interesting games are the ones that make you follow along as they evolve.

  • I agree with the general point, but I do have to wonder; isn’t there a market for games which are pretty much the complete opposite?

    Take the original Legend of Zelda for example. You get dropped in the middle of a large, fairly open world, get a sword and then pretty much get left to figure it out from there. Same sort of thing applies in quite a few other games from this era. As well as quite a few roguelikes and other niche games like Dwarf Fortress.

    There are indeed people out there who like being thrown in the deep end and figuring everything out through sheer trial and error. They’re just a somewhat niche audience whose tastes are pretty far from the mainstream.

    • Filip Wiltgren

      I agree as to the world aspects, but Zelda started off very basic: there wasn’t very much you could do with Link in those first moments. Then it ramped up the options, but never in such a way (as I remember it, been close to 30 years…) that you were ever lost.

      Imagine staring out with 50 different power moves, each of which needed a 5+ button combo. That would have been impossible to play (or at least very boring).

      The same is true in even monster games such as ASL. Yes, you’ve got a (literally) 3-foot stack of manuals but you start out with just a few troops on a small map when you start learning the game.

      Having said all that, yes, there’s definitely a market (albeit small one) for monster complexity games with huge decision spaces (or just look at the decision space of Go – with our strongest computers we haven’t managed to solve it yet).

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