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Because it is simply one of the most powerful aspects of fun in gameplay, we need to look more closely at choice as an aspect of fun. What makes a choice interesting versus uninteresting? How can you design choices that are more interesting than not?
One of the most important aspects of choice is consequence. For a game to engage a player's mind, each choice must alter the course of the game. This means the decision has to have both an upside and a downside; the upside being that it advances the player one step closer to victory; and the downside being that it hurts the player's chances of winning. This concept seems simple, but you'd be surprised at how many games force the players to make choices that have no impact upon whether they win or lose.
Remember, the player wants one thing more than anything else, and that is to win. Anything you do that is outside this scope runs the risk of alienating your audience. So when Sid Meier says "interesting choices," what he means is that the game must present a stream of critical decisions that either directly or indirectly impacts the player's ability to win. No matter what you've been told in the past, drama and suspense in games seldom come from the storyline. It comes from the act of making decisions that have weight, and the more weight each decision carries, the more dramatic the game becomes.
As a designer, this is what you must strive for. But how do you make the choices in your game have significance? To start with, let's step back and analyze your game. What type of decisions are your players making? Are those decisions truly meaningful, or are they tangential to the main objective? To help analyze this, we use a tool we call the decision scale, shown in Figure 1.
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Figure 1. Decision scale |
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If there are decisions in your game that seem "inconsequential" or "minor," you have a problem. Go back and rethink the choices you are giving your players. Is there a way to make those choices matter? And if there isn't, those choices need to be eliminated because they aren't adding anything to the game and are probably hurting the experience. Now take a look at the decisions higher up on the diagram. Is there a way to make some of your players' decisions fall into these categories? These are the types of decisions your players want to make.
But, unless your game is an arcade-style shooter, the decisions you ask your players to make shouldn't all be life and death. Nonstop action can get boring too--it's in the breather between waves of enemies that we can appreciate our accomplishments, anticipate the next wave, and steel ourselves for the battle ahead.
In order to create a truly engaging game, you want some peaks and valleys. Let the decisions rise and fall, and as the game progresses, ratchet up the tension by making the decisions gradually more important, until by the climax of the game, everything hangs in the balance.
Types of decisions
It's easy to say that games should have interesting choices, but why is one choice more interesting than another? The answer lies in the type of decision you ask to the player to make. If the player has to choose between two weapons, and one weapon is only slightly superior to the other, even though the player may be faced with a life and death encounter, the decision itself does not reflect this. To make this decision interesting, each weapon must have a dramatically different impact on the player's chance of winning.
But if the decision itself is too easy, then it's not a decision at all. If it's obvious that the player should use the golden arrow to slay the dragon, there's no real choice. Why would the player risk using anything else? This decision, although it appears to be life and death, is meaningless. The player will invariably choose the golden arrow, unless he doesn't know about its powers, and in that case, it's an arbitrary choice, not a decision.
The key to making this decision interesting is for the player to know that the golden arrow is the right choice, but also to know that if he uses the golden arrow now, he won't be able to use it later when he has to fight the evil mage. To make this decision truly dramatic, the player must be put in a position where both paths have consequences. If the player doesn't use the arrow now, his faithful companion, who is not immune to dragon fire, may die during the battle. However, if the player uses the arrow, it will be much harder to destroy the evil mage later on. Suddenly the decision has become more complex, with consequences on both sides of the equation.
Decision types
In the example of the golden arrow, the decision is a combination of the previous decision types. It's an informed decision because the player knows a lot about situation he is in, it's a dramatic decision because the player has an emotional attachment to his faithful companion, it's a weighted decision because there are consequences balanced on both sides, it's an immediate decision because it impacts the battle which is taking place with the Dragon, and it's a long-term decision because it impacts the future battle with the evil mage. All these combine to make the decision of whether or not to use the golden arrow a critical choice in the game, and this makes the game interesting.
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Exercise: Decision Types Take your original game and categorize the types of decisions you ask your players to make. Are there any hollow, obvious, or uninformed decisions? If so, try to redesign these choices. |
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Not all decisions in a game need to be as complex as the one with the golden arrow. Simple decisions are fine, just so long as they're not hollow, obvious, or uninformed. As a rule, you want to remove all nondecisions from you game, and a player should never be forced to think about anything unless it has some impact, either direct or indirect, on whether they win or lose.
Dilemmas
Dilemmas are the situations where players must weigh the consequences of their choices carefully, and in many cases, where there is no optimal answer. No matter what the player chooses, something will be gained and something will be lost. Dilemmas are often paradoxical or recursive. A well-placed dilemma and trade off can resonate emotionally with a player when encountered during the struggle to win your game.
Game theorist John Von Neumann used dilemmas as a framework for studying how people make choices, and how conflicts are resolved in both game-based and real world dilemmas. Game designers can use the same methodology to study the choices in their own and other designer's games.
To understand dilemmas, von Neumann broke them down into very simple structures, called moves. Each move was diagrammed on a matrix, showing the potential outcomes of each strategy as they pertain to each player. To understand this concept more clearly, let's next look at a classic dilemma with a simple structure.
Cake-cutting dilemma
A mother wants to divide a piece of cake between her two children. In order to avoid arguments about how large a piece each child should get, she makes one child the "cutter" and one child the "chooser." The cutter gets to cut the cake, and the chooser gets to choose which piece. If we assume that each child wants the bigger piece (i.e., wants to "win" the game), we can diagram this conflict to show the potential strategies for each player, the dilemma they face, and the payoffs for each potential outcome.
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Figure 2. Cake-cutting payoff matrix |
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As we can see, each child has two possible strategies. We know that it's impossible to cut the cake exactly in half; there will always be one crumb more or less on either side; but the cutter can choose to cut the cake as evenly as possible, or she can choose to cut one piece bigger than the other in an attempt to get the larger slice. Since we've determined that one piece will always be larger than the other, even if just by a crumb, the chooser also has two strategies. He can choose the smaller piece or the larger piece.
By looking at the payoff matrix created by combining these two possible strategies for each player, we can see that in this simple game, there is an optimal strategy for each player. Since we have said that each child will try to get the bigger piece, the chooser's optimal strategy is obvious--he will choose the larger piece. And, since the cutter is also trying to get the largest piece possible, she will try to cut the pieces as evenly as possible. The optimal strategies for each player meet in payoff #1: the chooser gets a slightly bigger piece.
The cake-cutting dilemma is an example of a zero-sum game. By this we mean that the total amount won at the end of the game is exactly equal to the amount lost. In this case, the chooser gains the crumb lost by the cutter. Because of the nature of zero-sum games, the interests of the players are diametrically opposed. What one player loses is gained by the other.
What von Neumann discovered in his study is that there is an optimal strategy for each player in games of this nature that will produce the best possible results in a given situation. He called this concept "minimax theory."
Minimax theory states that there is a rational way for players to make choices in a game, if we are talking about a two-player, zero-sum game. The optimal strategy for all players is to "maximize their minimum potential result." So, in the case of the cake-cutting example, while the cutter cannot "win" the game, her optimal strategy will still maximize the amount of cake she gets to eat.
Games that fall easily into optimal strategies may be interesting for mathematicians, but as game designers, they are often the kiss of death. If you present your players with a game as simple as the cake-cutting dilemma, they will always make the optimal choice and the game will play out the same way every time. How can we create dilemmas that are more complex, where the players must weigh the potential outcomes of each move in terms of risks and rewards?
A game that has a more complex payoff structure was created by two RAND scientists in the 1950s. Called the "prisoner's dilemma," it's a simple, baffling game that shows how games that are not zero-sum can create situations where the optimal strategy for each player can result in sub-optimal results for both.
The prisoner's dilemma
Two criminals commit a crime together and are caught by the police. For the purposes of our example, we'll call the two unlucky criminals Mario and Luigi. Mario and Luigi are held in separate cells with no means of communication. The DA offers each of them a deal and discloses that the same deal was made to his partner in crime. The deal works like this: if you rat on your partner, and he denies it, you can go free and the he gets five years. If neither of you rat on each other, the DA has enough circumstantial evidence to put you both away for one year. If you both rat, you will each get three years. Figure 3 shows the payoff matrix for each potential strategy.
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Figure 3. Prisoner's dilemma payoff matrix |
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Using the same process we used to determine the optimal strategy for the cake-cutting dilemma, we can see that the optimal strategy for Mario is to rat on Luigi. If he rats, he gets either three or zero years. If he doesn't rat, he gets one or five years. The optimal strategy for Luigi is also to rat on Mario for the same reasons. If both players choose the optimal strategy, however, they will both serve three years--more years total will be served in jail than in any other resolution.
The hierarchy of payoffs in the prisoner's dilemma is as follows:
The actual numbers in this hierarchy are not important. What is important is that they ascend in this order: Temptation > Reward > Punishment > Sucker. If this hierarchy exists, the optimal strategy for each player will always result in a payoff that is less than if they had acted cooperatively. Now, we are talking about a true dilemma--what will Mario and Luigi do?
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Does your original game contain any dilemmas? If so, describe these choices and how they function? |
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In a recent presentation at the Game Developers Conference, designer Steve Bocska of Radical Entertainment applied the hierarchy of payoffs in the prisoner's dilemma to a hypothetical game design in order to show the usefulness of game theory concepts to designing compelling dilemmas.1
Bocska imagines an online game in which two players are building and customizing spacecraft with a budget of $10,000. The game requires bartering and trading of raw materials, but at a high transaction cost: $8,000 of "shipping and handling" in a typical game round. A technology can be purchased that allows materials to be "transported" with no transaction cost--but in order for it to work, both players must purchase it. The cost of the technology is $5000.
Bocska asks, "Under these conditions, what is a player likely to do? If both players purchase the transporter equipment, they will reduce their transaction costs for the game from the usual $8,000 to a one-time cost of $5,000 for the transporter--a savings of $3,000. If, on the other hand, neither player purchases a transporter, the transaction costs throughout the game for each player will amount to the usual $8,000. What if only one player purchases the machine? With nobody else to connect the transporter to, their machine becomes effectively useless, resulting in them receiving the "sucker's payoff"--the cost of the equipment plus the added cost of continuing to barter using the traditional costly method ($5,000 + $8,000 = $13,000)." The payoff matrix in Figure 4 shows the results of the potential strategies.
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Figure 4. Transporter game payoff matrix |
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Unlike the prisoner's dilemma, Bocska envisions a game in which the players can communicate--negotiating with each other when and if to purchase the technology. This complex payoff structure creates a dilemma for the players that can make for compelling strategic moments and potentially deceitful or cooperative decisions play after play.
This is exactly the type of situation you should strive to create in your games. If possible, give the players dilemmas as part of the core gameplay. Make sure to tie the dilemma into the overall objective of the game. If you can accomplish this, it will make the choices much more interesting.
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