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Playing with Cause & Effect

During my time in the game industry, it has slowly dawned on me that perhaps the most interesting capacity of games is their ability to let the player explore a unique, consistent and mysterious relationship between cause and effect.

During my time in the game industry, it has slowly dawned on me that perhaps the most interesting capacity of games is their ability to let the player explore a unique, consistent and mysterious relationship between cause and effect.

When there is an action and an unlikely, or hard to decipher, reaction; – when the reaction does not fit into our heuristic of the normal, predictable rules of cause and effect – when a person has to try several times and with several different approaches to begin to understand a consistency between input and output, it is a deep source of fascination – because, as with everything, we demand that there must be some mappable network of logic linking the cause to its perceived effect.

Our fascination with understanding patterns has long since been the domain of science. But what if this fascination, these tiny sources of bewilderment, would begin to seep into the realm of entertainment? They can and they have. Interactive media can create these types of systemic mysteries – these obtuse logic systems – these (unnatural) natural mysteries – in ways that other types of entertainment cannot, if only because this category of entertainment requires the player to form a hypothesis and then test that hypothesis in their own ways. Patterns (and broken patterns) can appear in many different forms; and yet I am writing this because I think the capacity to let a player map out cause and effect in an unknown system is poorly understood, and goes vastly under-utilized in games and other forms of entertainment.

In this essay, I will try to provide examples of this phenomenon, which I will refer to frequently as “black box phenomenon” (and the larger theory as a black box theory of engagement), across many different modes of entertainment. Through these examples, please bear in mind that at this moment in the evolution of interactive media, we are only just starting to realize the potential of discovering natural laws in unnatural worlds, so the best examples may be yet to come.

Example 1
Flow: Red Dots and Blue Dots

*For this example, I will be referring to the Flash version of Flow, released as a student project in 2006.

Flow is a minimalist game experience where the player controls a small underwater creature. There are no explicit objectives, so the player must discover for herself the range of movement and possibility in this serene underwater environment. While exploring, the player will soon encounter other similar looking creatures, as well as red dots and blue dots. The player may initially avoid other creatures, but will soon discover that if she eats a ring from another creature, the new ring is added to her own creature’s body.

In the Flash game, the role of the red dots and the blue dots is not so easy to discern. When the first-time player eats a red dot or a blue dot, she may wonder how it effects the game world. The creature does not seem to grow, and no points are awarded; in fact, nothing seems to change. So what are these things? What do they do? And if they do nothing, then why are there two very distinctly coded colors: red and blue?

The answer is both subtle and simple. It may take a first time player a few minutes to decipher the pattern. In the Flash version of the game, when the creature eats a red dot, the blue background (the water that the creature is swimming in), changes by only a few degrees. Eat a red dot and the blue water becomes slightly darker (as if diving deeper). Eat a blue dot and the blue environment becomes slightly lighter (as if approaching the surface).

When I was playing the game in 2008, and realized that this might be the case, I had to test this hypothesis by eating only red dots, in succession, and then eating only blue dots in succession. In the Flash game, the creature does not react when eating dots, so it can take time to understand their purpose. This small mystery was sadly dropped when the game moved to Play Station. There are still red dots and blue dots in the PS version, but when eating a red dot, the player will see their creature dive deeper into the depths, so there is no confusion about the effect.

This is an example of playing with cause and effect in an unfamiliar environment. A nice little mystery, the answers to which seem playfully within reach.

In considering Flow, I can’t help but think of the glass vile in Alice in Wonderland. The glass vile has a label around its neck that says, “DRINK ME.” Alice checks the bottle to see if it is marked “poison” and it is not, so she drinks the mysterious liquid and soon shrinks down to a fraction of her original size. She then realizes that she has left a key on the table, and is much too small to retrieve it. Luckily, she finds a box with a very small cake and a note that says, “EAT ME.” She does, and she grows again. She is beginning to understand the relationship between cause and effect in this world, and as she becomes more familiar with these rules, she learns to use them in order to get the key and then progress through a tiny door and out into the garden.

In both Flow and Alice and Wonderland, we experience the consumption of a mysterious item. The player of the first example (and the reader of the next) are left to solidify a useful connection between cause and effect. It is odd to me that more games do not allow players to map these strange, but eventually navigable, relationships between a cause and its perceived effect. I should specify that many games do, but very few in ways that are carefully crafted and deliberately engaging.

Example 2
Don’t Starve: Encountering a Village of Pigs

In this beautifully sketched, procedurally generated landscape, the goal is to survive in the wilderness for as many days as possible, without starving, or eating the wrong foods, or getting attacked in the night, or aggravating the wrong animal. Life is actually quite fragile in Don’t Starve. Through mistakes, the player is taught to be somewhat cautious around new animals and new discoveries, because if the player dies, she risks losing everything and starting again from scratch in a new, randomly generated environment.

In Don’t Starve, most of the nature is recognizable. There are forests, dry meadows, rocky areas, swamplands and caves. There are also many animals that resemble animals in our own world, like grazing buffalo, frogs, butterflies and bees. But if the player explores a little further, the world can start to get a little strange. The player may start to encounter characters, animals and items that she does not necessarily know how to approach, or for which she has no useful preconceived notions that carry over from the real world.

For the purposes of this paper – about playing with cause and effect, and uncovering deeper and deeper algorithms – I will limit my discussion of Don’t Starve to a personal encounter of a village of pigs. While the previous example was about the consumption of a mysterious item, the following has more to do with discovering, and experimenting with, the social rules that govern a culture of animals.

Upon first finding a village of pigs, I came up with a couple of cursory observations. The pigs live in skinny wooden houses. During the night they sleep in these houses, and during the day, they make grunting sounds and walk around their territory, collecting any food that they find on the ground. If the player leaves food on the ground near the pig village, a pig will eat it and will produce manure (which can be a valuable resource in the game). The pigs also tend to get into fights with the spiders. The fight usually ensues when a pig, on his rounds, stomps through a spider’s territory. The spider, by its nature, is programmed to attack anything that ventures too close to its home.

One very late evening, I found myself spending time around a village of pigs. We had established a kind of, neighborly live-and-let-live agreement. In the game, a player can give different items to animals and monsters. So late that night (with pink rims around my eyes) I decided to experiment. I gave a pig a carrot. It ate the carrot, but other than that, nothing special happened. I gave a pig a shovel, and the shovel lay untouched on the ground. I gave a pig a flower and it ate the flower. I had some monster meat in my inventory so I tried giving that to the pig to see if it would have any effect. (There are hundreds of possible items in Don’t Starve, so experimenting with gifts can be a long process.) Expecting nothing, I was surprised when the pig started to follow me around. It even attacked a spider that I accidentally aggravated. The pig followed me around for another few seconds and then it returned to the pig village to resume its routine. I learned two valuable pieces of information from this experiment: 1.) giving a pig meat caused it to come to my protection 2.) there is a limit to the amount of time that it will protect me. I tried something else: I gave another pig two pieces of monster meat, and it followed me around for what seemed to be twice the amount of time as the first pig. When that experiment wore out, I tried getting a new pig to attack a spider for me. This time other pigs joined the fight. This was another valuable conclusion: in the pig culture, if a pig is fighting another creature in view, more pigs will join into the fight.

Through this series of experiments – and there are hundreds of other animals and items to experiment with in Don’t Starve – I not only discovered a few new socio-cultural algorithms at work in the ways that the pigs function, but I was also able to manipulate the pigs in a useful way; I found that if I could lure the pigs out of their village by sparking a number of fights with spiders, they would leave their loot unprotected in their village, which I could then steal in order to survive for a longer amount of time in the wild.

Don’t Starve is an algorithmically nuanced world, with characters and animals that work in a variety of ways. The game tells the player very little about all of these details of behavior. But these procedural mentalities can be found out, mapped, and potentially exploited in useful ways. The pig people have individual psychologies and their pig culture is governed by a set of rules. Like a blind person feeling out a new shape, the player must slowly feel out the full extent of these hidden algorithms. There are many other examples of playing with action and consequence in Don’t Starve. There are different types of mushrooms, for instance, that only reveal themselves at certain times of day – and eating certain varieties have certain effects on health and sanity. For another example, the Walrus people have their very own cultural tendencies, but I will leave that story for another time.

Anyone who plays Don’t Starve will say, “You don’t have to do all of this work! There is an extensive community wiki about the game, where people share their experiences and teach others how to survive! Use the collective knowledge!” I have stubbornly chosen not to read the wiki, because I enjoy mapping the universe through these small (often dangerous) forays of trial and error. Like an 18th century natural philosopher, I kept a notebook of all of my new experiences, findings and hypotheses.

In this paper, I am stepping through a few of these small, pleasurable experiences of wandering into the unknown, and pushing oneself towards a deeper and deeper understanding of an interesting and interconnected set of rules, that may (or may not), give way to a player’s success in the game.

An Interlude from the Examples
What this paper is, and what this paper is not

Like a programmer, I have to take a moment to “catch” a few exceptions that have no doubt been thrown in the reader’s mind. After all, Aren’t all games a matter of stepping into a new environment? Don’t all games involve deciphering patterns? Aren’t all games essentially a black box phenomena? What is it about these examples that sets them apart?

I have to be very careful with the examples that I provide. If I am not, then my argument gives way to a deluge of examples that may water down the main point. For instance, most point-and-click adventure games tend to devolve into a frustrating, recursive experiment of trial and error: Does the pie work to sway the inn keeper? No? Does the kitten? No? The glove? The carrot? How about the wood plank? It’s true, this mindless trial and error is a form of “playing with cause and effect” – after all, which item is going to produce the desired outcome of gaining entry into the inn? But this is not the type of procedural uncovery that I am interested in. In the point-and-click example, while the player may have begun the game thinking carefully about which item would make sense to give to the inn keeper, by this point, she has lost trust in the game but is still trying to push her way forward through forceful combinations. Frustrating, obtuse point-and-click adventure games, as well as impenetrable games that could have withstood just one more round of playtesting, while visible from our current trajectory, are examples where the creators are failing to carefully construct, or facilitate, an experience, or an environment, of systemic uncovery.

I am using this non-word because it contains “uncover.” I like the image of a player walking along and tripping over an algorithm, the full extent of which is buried under the dirt, and must be carefully excavated.

There are more examples that can push us further afield. In just about any game, there are plenty of patterns to watch, understand and hold in mind. In a stealth game, the player needs to watch the guard in order to understand his walking pattern and eventually sneak by. In a shooting game, the player must begin to form a hypothesis about how often the bad guys peek out from behind their sandbags. In a platformer, the player must watch an enemy going back and forth on a bridge in order to time the next jump. Every game is going to involve patterns. In A Theory of Fun, Raph Koster writes that the human mind is a “pattern recognition machine,” and that games are “particularly delicious patterns” that the human mind likes to “gobble up.” In all of the examples in this paragraph, the player is watching visual patterns. By contrast, the patterns that I am most interested in are more dependent on input, and output.

I am not just interested in games where there are patterns, nor in games that are about discovery, but in games where there is the discovery of an unspecified mechanism, or unspecified system.

One could also argue that, in games, there is always a black box phenomenon at work. The player does not look at the underlying code, so the player can only ever interact with the results of a mysterious system and has to inspect this visible layer for useful information.

I am trying to guide us away from the examples involving obtuse systems in games where the player simply can not figure out how the stupid thing works. (There are plenty.) Instead, I intend to focus on the examples that push us – just a little further – into new and interesting realms of entertainment. I am more interested in games that set these underlying algorithmic mysteries carefully and skillfully, inviting the player to form a nuanced understanding of an algorithm, which may prove handy later on. This type of systemic mystery, when done right, is a seduction of reason and rationality. Outside the context of entertainment, the player’s curiosity may otherwise be mistaken for a scientific impulse.

Extending from the smallest examples…

The simplest version of this type of cause and effect micro-mystery, might be something like…let’s say…entering a number into a computer terminal and receiving a different number back. If there is any good reason for doing so (even if there is not) a person might get stuck on this little conundrum, and start to carefully map different inputs and their resulting outputs in order to attempt to find a consistent algorithm that accurately constructs a relationship between the two. Here are a few more short examples:

  1. Imagine a person sitting in a restaurant. The person orders food, but the food is delivered to a different table. After visiting this restaurant a few times, the guest (or better yet, the whole restaurant working together) may be inclined to crack this two dimensional algorithm in order to receive the food that they would like to eat. (Example courtesy of Christopher Russell.)
  2. In the real world, a person finds a vending machine. The vending machine contains a gold bar in one of its rings. The person pops in several quarters and punches in the desired letter and number to retrieve the gold bar. But instead, the vending machine drops an item that was sitting in a different position. Becoming nervous, the user (with his limited number of quarters) has to decipher inputs and outputs in order to retrieve the desired item.
  3. Imagine a barren landscape. Underneath the dusty surface are valuable colored liquids. The player can not see under the surface, but can start to learn that different pockets of color under the ground are likely to attract different types of animals near the surface, or facilitate the growth of certain types of plants, or create special rock formations. Mining colors might be an expensive procedure in the game, but the player can begin to map these consistencies by trial and error, to form a reliable understanding of the ecosystem. 

These puzzles may sound a little dry for most people hoping to sit down with a game. But it is not these puzzles (in particular) that excite me. It is the implications of these puzzles. From the smallest examples, we can begin to extrapolate and to protract into larger and larger systems and larger and larger mysteries involving the increasingly complex (orgiastic) rulesets of an unknown environment. World-building is rarely taught and practiced at the level of unusual rule sets. (It is more likely to manifest at the level of art and graphics.) Yet, embarking on a venture of world-building we can start from a fundamentally different paradigm. To shift worlds we must shift systems. And to shift systems, we need to start tinkering at the level of cause and effect.

I have reviewed a few examples of these black box phenomena. I have even tried to make sure that the black box concept extends beyond digital machines and refer just as much to natural worlds, social rules and human psychologies. But who knows, maybe the future of entertainment will be a more literal black box: a device that you purchase and put in your home, without ever really knowing what it does.

The raw curiosity that accompanies these small, bewildering mysteries - mysteries experienced through an action and its unlikely outcome - have a deep and largely untapped potential in games. 

Coming Soon: Examples of Unknown Systems at work in Film and Literature (Dogtooth, Stalker, Sphere and The Infernal Desire Machines of Dr. Hoffman)

Follow me on Twitter: @taylorjames9

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