There’s multiple ways to look at games and frame them, one way is to study them as closed formal systems. Surely they are not entirely closed, since I don’t believe we can think of human players as elements in a fully closed system, but lets just analyze the game rules for now and so, view them as closed systems.
In this kind of systems, the relation between the system’s elements can generate an emergent behavior, and it’s wildly spread (ok, not so wildly) and I do believe that a good game needs some level of emergence. Part of the fun is the ability the player has to alter the game world (the system) and watch how the game world reacts, how does it changes and affects all it’s elements towards the game’s goal, for that reason, the way that the elements in systems communicates with each other is crucial.
Within a game there are many systems that regulate the flow of play, in the form of the rules, dynamically changing and transforming game elements, as would say Salen and Zimmerman in Rules of Play. That’s where I want to get to, a very special sub system, a way of communication between the elements, the feedback loop.
The feedback loop is like an abstract tool you can use to generate some kind of behavior in your game, but what is it and how can it help you achieve what you intended for your game? Our subject is some sort of collection of sub-systems inside the formal structure of the game that senses the game state, analyse if the changes activate any given bias and then responds activating a controller that changes the game state, closing a loop of feedback information!
I think the best way to understand feedback loops is through examples, so lets look at this entry at the Team Fortress 2 official blog, here’s an excerpt
How do respawn waves work? Is my respawn time affected by my performance? Why do they exist at all?
Respawn waves occur on regular intervals, based on the map settings. Most of our maps use a 10 second respawn wave time. That 10 seconds is then modified by the map state, generally reduced for the team that controls the most capture points. (…)
So here we can see a feedback loop sub system in action at Team Fortress 2: There’s some control tool that reads a subset of the game state, in this case, the number of capture points each team has, there’s another system that analyses if this state is above some bias (which team control the most capture points) and finally a mechanism that apply a adjustment to some element in the game, in this case, reducing the team’s time to respawn. This change will end affecting the game state back by making the life of the winning team easier a bit, helping them and driving the game to a conclusion, as they keep the larger number of capture points, the team’s respwan time is kept reduced, or as said in the original post:
“They provide a reward for the team that’s doingwell, in that ifthey wipe out a significant amount of the enemy team they’re rewarded with a short grace period in which they can achieve objectives.”
Now that we understand what a feedback loop is, we should note that they can be divided into two categories:
- Positive Feedback Loop: Encourages the system to exhibit ore and more extreme behavior by rewarding the actions that drive the system out of stability, like the case in team fortress 2 where a team that’s already winning gets even further advantages.
- Negative Feedback Loop: Those are stabilizing and bring the system to a fixed, steady state. A nice example is Mario Kart Wii, where the player that’s in first place never gets the best power ups from the “?” boxes while those player that are in the 2 last places always get power-ups that gives them a great boost, this mechanism prevents the player in first place to get too much ahead and the last positioned from being too far behind, which encourages a close and more competitive race.
Several boardgames use negative feedback loops to keep the player toe-to-toe with each other until the end. A fine example is Power Grid, a game about supplying cities with electricity, the first player to supply a certain number of cities is the winner but, every turn, the play order is changed so the players that supplies most cities are penalized in several ways, keeping the competition very tight until the conclusion.
The scholar Joris Dormans used Power Grid as a case of study for his Visualizing Game Dynamics and Emergent Gameplay article, in wich he proposes an UML model to describe the relation between elements in the game system, a model to analyze the emergent gameplay with a special notation to feedback loops, great article!
It’s important to notice that a game usually has more than one feedback loop, take the Power Grid example, the main structure of the game is a whole positive feedback loop: you buy plants to generate electricity and power up cities so they pay you, with this money you can buy more and better plants to power up more cities to get more money and so forth. This loop is the heart of the game and it pushes it towards a conclusion, but besides this one we can find the negative feedback loop aforementioned that keep the runway leaders at bay.
We can use the feedback loops as tools to achieve a certain tendency in a game:
- Positive feedback loops usually destabilize the game, drive it to an end, magnifies early success
- Negative feedback loops on the other hand stabilize the game, prolong it and magnifies later successes
But due to that kind of behavior, you need to have some care using this abstract tools in your game
- The positive feedback loop can drive the game to a conclusion too early, or even worst, help one player get so far ahead that his/her opponents lose all hopes of catching the leader, like in the kids game Chicken Cha Cha Cha players move around in a circuit by memorizing a number of tiles, every time the player reveals a tile with the same illustration as the one in front of it’s chicken, that player can move one space and then play again. So as long as he/she keeps finding the correct tile (what can be done buy memorizing those that were opened early) he/she can keep playing until win, without giving a chance for the other players. Although it can be fun for the player in the a winning streak, it can be very frustrating for those that are only watching the other to play. Fighting games developed at the same time a kind of positive feedback loop and an answer to a problem like in chicken cha cha cha, at certain point, combo system were added to fighting games, it’s very rewarding for a player to land several blows in sequence, while keeping that sequence the opponent can’t defend (positive feedback loop), so, in theory, the first player to start a combo could keep it until defeating his opponent, but it never happened, because that fighting game designers always made this system limited: combos always end after a streak of 5 to 7 blows, even if the attacking player hadn’t missed anything, limiting thus, the effect of the combo positive feedback loop.
- On the other hand, the presence of negative feedback loops in your design may make the players feel that are out of control, or feel they’re being penalised for a good performance. In the fourth incarnation of the famous RPG series, Elder’s Scroll Oblivion, Bethesda Software created a system in which every encounter in the game is always on par (levelwise) with the player’s character. Theoretically a very nice solution for creating a truly open world, without any kind of high level area in which the character can’t enter until reaching a specific level. We can think of this system as a negative feedback system, as the player keeps advancing his character, the creatures in the game’s world advance as well. It was designed to make every encounter worthwhile, to make the player feel challenged at each fight, but it had a side effect: due to this system, most of the players felt that they were not advancing anything, they couldn’t feel the power-curve, which is an important feature in RPG games. It was like “the same small goblin that killed me when I was level 1 is still giving me a headache now that I’m level 10, doesn’t matter if a level so”. The same system is in place in Fallout 3, but this time, it was highly tweaked so not all foes were evolving at the same rate as the player.
We are excluding form this discussion the players’ mind, which is always adapting and adjusting his plays during the game, we excluded the observer from the system, but even though, this kind of analysis is very useful for game design.
Now that we had this discussion I’ll try to identify feedback loops inside the games’ rules in the design analysis I plan to do in the next weeks.