Monthly Archives: July 2020

The Illusion of Control, Part 2: Chrom Fireemblem Is A Dirty Cheater

Posted on by Jeremy Geist

Welcome back to my 2-part article series about various methods to disguise the variance in your game to give your players an illusion of control. You can read part 1 here.

There’s a very understandable revulsion to “being manipulated” that makes this subject a little strange to write about. After all, we can’t pop open the news without finding another grim headline about how our personalities and behaviors are largely the product of market forces that have been influencing us since we were children. The idea that a game, which we often play to reclaim a sense of control, is also “cheating” in a sense, can feel slimy and disheartening.

The key is that a well-designed game engages in manipulative behavior purely for the player’s benefit. A “fair” experience that doesn’t lie to or manipulate the player can often feel stark or brutally economical. This is especially true in video games, where nearly every game cheats, usually in the player’s favor, in order to better fit the model provided by human cognitive bias. The random number generator used by the Fire Emblem franchise is a nice, simple example: By using the mean of two RNG numbers to determine hit chances, it makes a 75% chance to hit “feel” more like how we think a 75% chance to hit should feel.

Just like how media is a safe way for audiences to experience emotions like fear and distrust that would be dangerous in the real world, it’s also a good space for creators to try psychological tricks that would be unethical outside of the game context. Of course, this applies only to techniques used within the “magic circle” of the game environment; manipulating your players into, for example, constantly paying for microtransactions in a mobile game falls back under the umbrella of questionable ethics.

Anyway, let’s look at some more techniques that I didn’t cover last time.

Chess: Disguise Variance Through Many Non-Variant Moves

Despite being a big-brain game for smart people and bad guys in action movies, chess and games like it have a fair amount of variance. They must have, because otherwise every single chess game between the same two high-skill players would turn out the same. However, chess has no “luck” per se beyond determining which player goes first; players are in total control of every piece at all time.

The trick is that players create variance through minute decisions that eventually compound into unknown game states. The average game of chess between high-level players is about 40 moves long; if you consider, for example, how moving a bishop two squares or three squares completely changes what pieces it threatens, you can see how each small move eventually creates a relatively novel gamespace. “Perfect information” Hobby games like Terra Mystica that use this form of variance go even further, with hundreds of individual decisions adding up to a game state that’s different even with identical setups, character selections, and players.

In a way, this method of creating variance isn’t an “illusion” of control – it is control. But it falls under the banner of this article series because it sneakily adds variance into a state where everyone involved is being perfectly rational. Instead of dice or a deck of cards, these games use the human mind as the ultimate random number generator.

Ra: Trick Players Into Logical Fallacies Through Weak Evidence

Humans are subject to several common cognitive biases. Many, many articles have been written about them, partially because they’re fun to write and partially because trying to rid yourself of them is a good step on the road to self-improvement.

But as game designers, we’re not out to force our players to change how they think; it’s better to go along with human nature, which includes human cognitive biases, and provide a game environment that works the way it “should.”

As an example, let’s look at the classic Reiner Knizia auction game Ra. In Ra, players draw tiles out of a bag and place them up for auction. Any tile taken out of the bag never goes back in; it’s either discarded at the end of the round or kept in a player’s tableau for end-game scoring.

This allows players to predict the outcome of future rounds based on previous rounds; for example, if you haven’t seen a lot of flood tiles, you might be more bullish on Nile tiles (which need flood tiles to score). If a lot of Ra tiles, which immediately start the auction, are drawn, you can be greedier and draw more tiles in hopes that you can bid on a better lot. These tiny edges might add up to an eventual win at the end of the game!

There is one problem, however: Everything in the last paragraph is a lie! There are so many tiles in the bag that the distribution isn’t substantially affected even if weird draws occur. To use the flood tile as an example: The bag has 180 tiles in total and 12 flood tiles. Let’s say you draw half (6) of them in the first round. If you drew 40 tiles total that round, in the first draw of the next round you’ll have a 6 in 140 chance to get a flood. That’s about 4 percent. The odds of drawing a flood tile as the first tile in the first round is 12 in 180, about 6 percent. So even though you drew half the flood tiles, the odds of getting more is changed only by an imperceptible amount that doesn’t really affect your strategy.

(Yes, I know I basically threw out a number of total tiles drawn at random, but 40 is my rough estimate for the number of tiles drawn in an average round. I’m more trying to illustrate my larger example.)

However, the odds have changed to a small degree, and enough of a degree to trick players into the gambler’s fallacy – even players who would normally know better. If you bid low on Nile tiles in a later round because you saw so many floods, you feel like you won because you knew there weren’t many left (ie. you weren’t due for one), even though the real reason was that the bag pulls worked the way you thought they’d work. Even better, if you do end up pulling more flood tiles, you can just blame the whims of fate for creating such a freak accident.

And you know what? This rules, because it works the way your mind wants it to work. Instead of fighting our brains’ incorrect perceptions all the time, we get to send them to Cognitive Bias Fantasy Camp, where we really were due for that flood tile. By using this method, games can have their cake and eat it too: We get variance, but we also get enough reason to believe that we can predict what happens next that we don’t feel like we lost because of luck.

Conclusion

As a designer, your responsibility is to make a game environment that’s fun for the player without being exploitative. Your responsibility isn’t to make a game environment where everything is as it seems. Just like how audiences accept that a stage magician is tricking them somehow, they’ll accept the same from your game, as long as you entertain them. I hope these tricks to disguising variance help you do so.

The Illusion Of Control, Part 1: The Ellen Degeneres Slot Machine

Posted on by Jeremy Geist

About a year ago I went to Reno on vacation. While there, I took a look at some of the slot machines that were located in the casino-hotel where I was staying and in the airport as well. One thing I noticed that every modern slot machine had in common was the complexity of their rulesets. Each machine had enough rules to take up three to five pages on a large screen, and used terminology that even I, a certified Brass: Lancashire owner, had trouble parsing due to lack of experience with the genre.

I eventually ended up spending $5 on an Ellen Degeneres Show-themed slot machine that had become something of an ironic fascination among my friends. The experience was quick and bewildering – lots of stuff was going on on the screen at once and I had a hard time figuring out anything beyond “the symbols line up sometimes, by the machine’s definition of ‘line up’.” It was an experience that demonstrated that you needed to spend significant time with gambling master Ellen Degeneres to understand her intricate system of rules.

I found this interesting because slot machines’ clientele skews heavily older, a demographic that’s significantly less willing to learn in-depth rules for a game. (Incidentally, younger gamblers are increasingly drawn to more “skill-based” slot variants; slot game designer Edvard Toth wrote a really interesting article about designing them.) This includes slot machines with broadly appealing themes like Sex And The City and the 2010 Sherlock Holmes movie. So why, if slots are trying to attract a wide range of people at all ages and experience levels, are the rules so dense and complicated?

Part of this is because the mathematical models behind different slots are genuinely different, particularly in how often they pay out and how their payouts are distributed. (This Gamasutra article by Timothy Ryan goes into that in more depth.) But I suspect another component of these complicated rules is providing players with, not actual control, but the illusion of control.

Slot machines can’t genuinely reward player skill because by definition they’re luck-based machines. But what they can do is provide, through rules, the illusion that your greater familiarity with the game will result in better payoffs. All these rules must mean that something you did, something perhaps as minor as choosing how many rows to play with, had a genuine impact on how the slot machine plays out, though of course we know it doesn’t really.

As it turns out, providing players with the illusion of control is a valuable concept in tabletop design as well. Variance is an immensely useful tool for creating unique game states and providing replay value, but players like to feel smart and in control and get frustrated when variance takes that away from them. So, like video slots, designers can find ways to disguise variance to make it more palatable to players. Here’s a few ways you can pull that off.

Rock-Paper-Scissors: Disguise Variance Through Player Input

One of the most tried and true methods of hiding variance is by making the player the random number generator. Take rock-paper-scissors, for example; even though the outcome of a normal game of RPS is mostly random, players feel like they have agency because they get total control of which sign to throw.

There are many, many games that use a simultaneous selection mechanic; this provides a healthy amount of variance, as the game states that result when players don’t know what their opponents will do are much more diverse than those that occur with total knowledge. It also has the beneficial side-effect of making player decisions easier because you have less open information that you need to take into account when making a decision. Despite Go Nuts For Donuts having a lot of moving parts, Gamewright (which mostly publishes games for kids) published it because having most gameplay be reliant on other players’ hidden actions made it almost as beneficial to throw out a number at random as it was to deeply consider the other players’ behaviors.

An interesting component of this illusion is that it becomes closer to real strategy the fewer players there are. Libertalia with three players really does provide a lot of opportunities to figure out what your opponents are going to play based on the pirates they’ve already played and the booty tokens they’ve accumulated; Libertalia with six is a clown fiesta where there’s so many moving parts it’s impossible to make a good guess. This gradient obscures how much of simultaneous selection is strategy and how much is luck.

Cockroach Poker: Disguise Variance As Bluffing

This one’s very clever, because it’s a system of logical strategic moves based off a faulty core assumption: That people can successfully tell if someone else is lying.

A great deal of scientific research has demonstrated this not to be true, but what’s important for us as game designers is that it feels right. When you successfully guess if someone’s lying about being a bad guy in Resistance or smuggle contraband goods in Sheriff of Nottingham, you don’t feel like you got lucky; you feel like you outsmarted the other player.

A special shout-out goes to the delightful Cockroach Poker, a game built almost entirely on the illusion that you know whether your friends are bluffing. (A quick primer: The game has eight suits of cards. In turn, players place a card face-down in front of another player and claims what suit it is. That player has to guess whether the claim is true or false.)

This illusion is built in two ways. The first is that the game allows players to pass cards to each other and restate what the card is. Even though this only serves to flip the coin again, it gives the illusion of more evidence to determine whether a player is bluffing, as you can read the bluffs of multiple players. You can also team up with opponents to confuse a “target” player with a chain of bluffs.

The second is through weighted decisions. When a player incorrectly calls a bluff (or someone bluffing gets caught), that player puts the card face-up in front of them; whoever collects four cards of the same suit loses and the game ends. This means that when you put a card in front of a player with, say, three stink bugs, and claim that it’s a fourth stink bug, that player is taking a much larger risk by doubting the claim, which would make them lose the game.

The thing is, however, this secretly makes Cockroach Poker a press-your-luck game more than a bluffing game. Instead of asking “is my opponent trying to intimidate me?”, subconsciously, Johnny Three-Stinkbugs has to decide “is the off-chance this card really is a stinkbug worth taking the risk of doubting it?” Then, when Johnny doubts it and is proven right, he gets both the thrill of gambling and the feeling that he’s a deductive genius.

To Be Continued…

This article ended up getting really long, and I have more methods of creating the illusion of control, so I’ll be posting a followup in two weeks. Look forward to it!

(Read Part 2)