I don’t get to do a lot of game development these days (now that I am a dad and I have a full time job). But I still think about game design a fair bit in my spare moments. Arguably, The Death of the Corpse Wizard is a strategy game and I enjoy talking about strategy game design in particular with the Keith Burgun Games community. There are lots of ways of talking about this subject (and I might even believe that at a fundamental level, one can’t make a good game of any kind via reductive strategy) but I, personally, find my thinking is influenced by two sources: philosophy and physics.
In particular, Bernard Suits’ book “The Grasshopper” has left a lasting impression on me, both as a kind of literary work and as an organized and systematic attempt to define what games are. I think this kind of philosophical approach can be useful for understanding even specific sorts of games, like strategy games, and I’d like to sketch an approach to the problem in that style here.
First, let me recapitulate some of Suits’ basic ideas. He defines a game as “The voluntary pursuit of a goal by less than efficient means.” This is a compact definition and thus requires some exposition. His frequent example is golf: the goal in golf is to put a ball in a hole. When we play golf we do not pursue this goal in any way. We intentionally pursue it by the less then efficient means of swinging a stick at the ball, as many times as necessary, until it lands in the hole. It seems obvious that golf only constitutes a game if we undertake it voluntarily. I have more to say on this point, but I think its reasonable to suggest that while we may go through the motions of a game with a gun to our heads, we can hardly be said to be “playing.”
This is not much remarked upon in The Grasshopper, but I think there is a reasonable implication in Suits’ definition: a game is an undertaking which is pursued for its own sake. This is plausible if we step out of the game and watch a person play: if a person voluntarily pursues a goal by less than efficient means, it must be because the less than efficient means of pursuit are themselves the object of the behavior. After Suits, I believe it is fair to provide the following description of leisure: any activity undertaken for its own end. Thus, games are naturally leisure. We undertake the pursuit of the goal for the sake of the pursuit rather than for some external purpose.
(This helps us understand the requirement that the undertaking be voluntary: if we were coerced by violence to play the game, we would be undertaking the activity as a means of avoiding violence, not for its own sake).
Can we understand how to design better games by considering this frame?
Strategy and Strategy Games
By the above, we might suggest that when someone plays a strategy game, their goal is not to satisfy the win condition of the game. For instance, in Chess, the win condition is that the opponent’s King is in Check. But a player who simply re-arranged the pieces when their opponent is not looking isn’t playing Chess, though they are pursuing the goal of Chess. To want to play chess is to wish to reach that goal by a highly restrictive set of less than efficient means. (Suits uses the word “lusory goal” to suggest this ancillary character for the in-game goal).
Can we put a finer point on the true goal, then? Yes – the purpose is to play. If we restrict ourselves to more specific sorts of games, we can give more specific answers.
When we play strategy games our goal is to strategize. When we design strategy games our goal is to furnish a context in which the player can strategize.
Thus, to understand our job as a game designer we need only understand what it is to strategize. Simple stuff first: to strategize is to construct a strategy. What is a strategy? I’ll provide my definition here, though it doesn’t differ much from the ordinary one:
A strategy is an efficient, robust, plan.
A plan is an algorithm which takes you from some starting state to a final, desired state. A recipe for chocolate chip cookies is a plan, but it isn’t a strategy. That is because it is not robust. That is, if you find you don’t have 2 cups of flour on hand, the recipe has nothing to say about the situation. Your lack of flour is a condition for which the plan has no contingency. Robustness is a probabilistic notion: a robust plan succeeds at reaching the goal frequently when you apply it over and over again in varying situations.
An exhaustive search of the state space of the traveling salesman problem is a plan as well. But it isn’t a strategy (or it is a very, very poor one) because it isn’t efficient. Efficiency relates to the fact that there are limits on our ability to make decisions (most of the time this limit is most concretely understood in terms of time, but it might also be something like ability – we simply can’t exhaustively search the state space of Go, for example). Most generally, humans have a limited ability to exert themselves towards any end. Thus, we seek to marshal our efforts by virtue of efficient plans. This is particularly true in competitive games – if a strategy is strenuous to apply, chances are you will eventually fail to do it, at least partially.
We can already get some juice out of this definition, as strategy game designers. Our games must have one or more goals (so that the player can strategize towards them). But that isn’t enough – the game must have one or more sources of variability (I’m purposefully avoiding the word randomness here). In a system without uncertainty of some kind, a plan cannot be robust because there are not varying situations over which we can test it. We might also say the robustness of plans in such a system is trivial or degenerate – all successful plans have an equal probability of succeeding: 1. Without variation in play, the player can only ever improve the efficiency of a given plan and in those circumstances they are engaged in a different activity: algorithm design. This may be leisure in some circumstances, but it isn’t strategy generation.
What about the notion of “efficiency?” First, let’s eliminate a possible source of confusion. By efficient, I don’t mean that the plan itself arrives at the goal in some limited number of turns or some other unit. Such lusory efficiency is probably a desirable property of a strategy, but I mean something different by “efficiency” here. What I mean is that the process by which the current game state is transformed into the next action is efficient. That is, it makes good use of the player’s limited cognitive resources. This corresponds to the intuition that a good strategy doesn’t have a lot of fiddly bits, that it abstracts the true degrees of freedom in the game into effective degrees of freedom.
A trivial example: suppose we fire a virtual cannon and we want to know where the ball will land. The worst possible strategy is to memorize the table relating angle and powder volume to the final displacement. A better strategy is to understand Newton’s laws and energy conservation, which profoundly limits the amount of information you need on hand to predict the final state of the cannon ball. Firing a cannon allows this kind of simple strategy formation because the apparent degrees of freedom are redundant in specific ways that you can learn.
Thus, if you want to design strategy games you need to present the player or players with apparent degrees of freedom which contain much simpler dynamics that they can learn. The true dynamics of the game should emerge from the basic rules. These true dynamics might only be approximate, they might only apply in certain circumstances which the player also learns to identify. But the key idea is that the player needs a system which is not just complex, but which is complex in a specific way that allows approximations to be valid in some domains.
Space is a perfect example (which explains why it appears as a game component in so many games). In some fundamental sense, in a real time game, for instance, to predict everything in advance you need to track each object and figure out its update rule on each time step. But many objects move in straight lines at a constant velocity and thus can easily be projected ahead in time. What other sorts of mechanical contrivances have this property?
So far we’ve just recapitulated standard game design advice. Can we generate some novel insights?
Its more or less standard lore that games should not be calculation heavy. I’d argue this general advice is malformed and the above definition produces a deeper insight. In a good strategy game calculation should eventually yield to approximation. Systems should be designed such that calculation should reveal one or more effective theories that apply in a limited number of circumstances. The effective theories can’t be “at the surface” because otherwise they would be trivial – its not a strategy if you are certain about which effective theory you need to put into place upon initial contact with the game system. Experience and lugubrious thought should be required to transform knowledge of the basic rules into a suite of personal effective theories along with heuristics facilitating choice among them. This activity of generalizing knowledge of game state and how to choose appropriate generalizations given the knowledge you have is precisely the activity of strategy formation.
This is why, for instance, adding a timer to a game to prevent calculation doesn’t solve the problem in many games. The true problem is that there are no effective theories embedded in the low level game rules, not that players have too long to calculate. Because a strategy is necessarily (or, by definition, if you prefer) efficient, merely adding a time limit doesn’t make people strategize. It just cuts off calculation. On the other hand, if there are accessible, effective theories, then players will naturally gravitate to them because of their efficiency. Don’t add timers: adjust the basic rules to make strategy more efficient than calculation.
Another insight generated by this strategy is that fun appears nowhere in the definition of a strategy game. Leisure is a much more expansive notion than “fun” and, I’d argue, we can’t really understand what strategy games are, in particular, if we restrict ourselves to those activities which are merely fun. The pleasure of learning a strategy game involves, in part, struggle, precisely because the true effective theories upon which we should base efficient and robust planning are obscured, in part, by the surface rules of the game.
This definition of strategy gaming doesn’t surface goals – there may be one or more goals as long as they are not degenerate (eg, as long as one is not the obvious, easier goal). These goals may be boolean or score based (though for reasons I won’t elaborate upon here, I think boolean goals are better).
A strategy game is a context for strategization, the production of strategies. A strategy is an efficient and robust plan. In order for a plan to be robust, it has to withstand unanticipated changes, and thus a strategy game must involve one or more types of uncertainty over which plans can be evaluated. In order to be efficient, a plan has to abstract over details of the game state – it has to free the player from managing all the minutia of the game state in favor of one or more appropriate, high level, conceptions of the game. Players naturally want efficient plans because they are less strenuous to apply and thus provide a natural advantage. Both efficiency and robustness imply a variety of conditions on the system in which the game functions: it must be variable and it must admit summary representations.
My hope with this approach is to highlight the fundamental features of strategy games rather than their superficial elements.