Game logic and representations, not mechanics

This blog post has been moved from https://creatingboardgames.wordpress.com/2021/11/27/game-logic-and-representations-not-mechanics/.

The Ludology podcast was a great way for me to get into the world of board game design. I recently got all the way to the most recent episode, which means that I’ve probably listened to 250+ hours of interesting discussions about board game design.

The first 100 episodes or so focuses pretty much on game mechanics. (Most of this, and probably more, can be found in the book Building Blocks of Tabletop Game Design: An Encyclopedia of Mechanisms.) I’ve been waiting for an episode where the concept of “game mechanics” is scrutinized and where “the logic” is separated from “the physical shape”. The hosts come close to discussing this several times, for example when talking about area majority as some sort of auction, but they have so far not dissected the actual concept of game mechanic.

That’s what I want to do in this blog post. I want to suggest game logic and representations of game logic as useful ways of looking at – or perhaps even replace – game mechanics.

Example 1: African Star

To make my point clear I’d like to discuss a few examples. The first one is African Star/Diamond Hunt (known as “Den försvunna diamanten” in my part of the world). The central game mechanic is quite simple: Players travel across the African continent and flip tiles that are placed on cities, in hope of finding the diamond named the Star of Africa. There’s a bit more to the game than this, but not very much.

The game logic of this part of the game has a few characteristics, where two important ones are that the probability of finding the Star of Africa is the same at all locations, and that players have no way of getting information about the tiles in advance.

This game logic could be represented in a number of different ways, for example:

1. A shuffled deck of cards, where players draw the top card to see what treasure or event a city holds.
2. A bag of tiles, where players blindly draw a tile.
3. Shuffled cards or face-down tiles, where players select which card/tile to draw.
4. Face-down tiles placed randomly on the cities of the map. The player may only flip the tile at the player’s location.

From a game model point of view, all of these are exactly the same. If you were to create a computer simulation of the game to get statistics of 2500 games, all of these would give the same result.

From a player point of view, though, they are very different. Some observations:

• Number 1–3 signals clearly that it does not matter which city the player goes to (when it comes to chances of finding the Star of Africa). Go to a new place and you get a chance to find the diamond, which city is unimportant. Whether you find the diamond or not is more or less predetermined – not very dependent on the actions you take.
• Number 2–3 signals that the player can try to find the diamond, and may anguish over whether to select one or the other tile/card or feel skillful when picking the right card/tile. (Representation 3 does this more than 2, I would argue.) The actions the player takes matters when it comes to selecting one tile/card or the other, but not which city the player travels to.
• Number 4 signals that the key to the game is to find the right city on the map. Players may feel angst when deciding where to go, and feel skillful when it turns out that they made the right choice.

Going for representation 4 fits well with the game theme/story, and also makes the game feel more exciting (as it gives the appearance of more agency for the players).

Example 2: A special kind of auction

Imagine a game whose only mechanic is a special kind of auction. The game can be described like this:

• There are three kind of goods to auction: coal, steel and engineers.
• There are in total thirty coins used for bidding for the goods – ten for each type, with values 1–10.
• The game is played in four cycles. At the start of each cycle, all coins are handed out. These determines the players’ resources for each type of good. The players only knows the types and values of their own coins.
• The starting player states which good to bid for by placing a coin for that good in the auction space (at the middle of the table). This is also the initial bid.
• Bidding continues clockwise. During each auction, a player may only bid once. Only coins belonging to the right good counts – if the player has no such coins, she must discard coin of choice.
• The player who wins the auction gets a good of the corresponding color, and also becomes the starting player for the next auction.
• The cycle continues until all coins are spent. The player with the highest total number of goods gets a victory point. Then the next cycle starts. The player with most victory points after all four cycles is the winner. Ties share victory.

It sounds like a fairly complex auction game, that could contain some interesting emergent strategies – right?

Now try tweaking the game. Let’s have 13 coins for each type of good, and let’s have four types of goods. And let’s call the goods spades, hearts, clubs and diamonds. Now you have a standard trick-taking game.

You may or may not already have figured out that this was a trick-taking game in disguise, or you may have gotten lost (or bored) by the convoluted game description. But the point of this thought experiment is to say that a trick-taking game is – in some aspects – an auction game. If you frame it as an auction it comes with certain expectations. If you frame it as a trick-taking game, you get a lot of pretty complex rules for free.

Auctions and trick-taking games could have the same game logic, but the way the logic is represented is very different.

Example 3: Worker placement

Worker placement is characterized by players having a number of workers which are placed on action spaces, after which the player carry out the action and the space becomes inaccessible for other players. Once all players have placed all their workers, they are returned and the procedure is repeated. (There are of course tonnes of variations of worker placement, but this is the plain vanilla version of the concept.)

The same game logic could be represented by action cards in a shared pool. The first player takes a card, and does the action described on the card. Then the next player, and so on, until everyone has selected (say) four cards.

Would it still be a worker placement game, though? This is not a trivial question. The mathematician in me says yes, since it is isomorphic with worker placement. The game designer in me says maybe – it depends on what we mean by worker placement. Do we mean actually placing meeples on action spaces, or do we mean the kind of games we get when utilizing such mechanics? The feeling of worker placement could both be there and not: The feeling of having to choose between two good actions and assess which one is more likely to still be there next time around is there. The feeling holding your workers in your palm, and feeling the number decrease, is not there.

If you describe it in terms of game logic and its representation, though, we can conclude that the game logic is worker placement. The representation is not.

What’s the point of talking about game logic and representations?

So, talking about game logic and representation, instead of (or in complement of) game mechanic, makes it easier to talk about “worker placement by picking cards”. For me it is a bit annoying that “game mechanics” sometimes refers to the appearance of a game, and sometimes to the underlying logic. Talking about “game logic” and “representations” makes it easier to cut right to the heart of the matter (regardless of which of the two it is). But changing perspectives takes effort and isn’t always fun, so there should be more to win than just making me less confused.

Consider example 1 again, where players search for the Star of Africa. I described four different representations for the same game logic, and the fourth was the natural choice for the game. Except that it most likely wasn’t a choice. The game designer probably didn’t look at other ways of representing the same game logic. For this particular game the natural choice was probably also the best choice, but this might not be true for other games. A game designer that separates game logic from representation has better chances of finding representations that fit the game, and also has another tool for investigating what fits and does not fit with the game. “Having a face-down tile placed at each city is great in this game, because X, Y and Z.”

A special case of finding well-working representations is when representations makes the game logic easier to understand or use. A worker placement game utilizing “place meeples on action spaces” can easily allow varying numbers of workers, and actions that require multiple workers. A worker placement game utilizing “select cards from a shared pool” can more easily allow actions being upgraded or taken out of game once used. Separating game logic and representation can help finding ways of making complex rules easy to use.

Another special case worth mentioning is when representations can play into multiple game logics. What if the workers placed are not meeples, but the dice players already use? What if tiles in a game are replaced by the game’s resource cards? Or the game board is replaced by card stacks? Having physical representations that feed into multiple game logics can be elegant and cost effective, and can also help finding new interesting ideas for a game in development. Detaching representations from game logic makes it easier to find synergies in components. Card game logic does not require cards. Game logic corresponding to grid movement does not require a grid board.

Finally I’d like to mention that separating game logic and representation makes it easier to notice and evaluate the actual logic in the game. Cards and dice are both (often) randomness generators. Dice give the same probability distribution every time you roll, while cards may be taken out of a deck once drawn – thus altering probabilities during the play. Which game logic fits your game best? Monetary income and harvesting resources might, when representations are peeled off, follow the same game logic just with slightly different values. Should they become more similar, or more unique?

Well, those are my thoughts for now. Feel free to comment with your own.