作者：Soren Johnson

2009年3月11日，在《Three Moves Ahead》（游戏邦注：这是flashofsteel.com的一个邀请资深玩家讨论策略游戏的播客节目）中，自由记者Tom Chick叙述了后来被称为“Chick抛物线”的现象：

我对《帝国：全面战争》的感情可以概括为一条抛物线。一开始，我不喜欢这款游戏，所以我对它的好感处于抛物线的底部。我不喜欢它是因为开发者的指南文件做得太糟了—-如果你想学会什么东西，你就必须按开发者的意思玩完脚本战役；工具提示也相当怪异。所以，我讨厌这款游戏。

Empire_Total_War_cover_art（from wikipedia）

但我继续玩，继续学习它，我就开始喜欢它了。可以说我对它的好感一直上升。就在我处于好感抛物线的顶端时，我觉得我已经理解它了，我喜欢它。但之后我开始发现游戏的AI很烂，使游戏显得非常迟钝。因此，我渐渐下降到好感抛物线的底部；最终我便不再对这款游戏有兴趣了。

通常来说，这就是我玩游戏的好感变化历程。一开始不怎么喜欢，之后随着精通游戏，我也开始失去兴趣—-除非游戏有比较好的AI，才能让我的兴趣不至于完全丧失，因为我发现对系统的精通意味着挑战的结束。一旦我达到那个点，对我来说，游戏就死了。我讨厌那样！那应该游戏应该再次起飞的时候。

许多资深玩家都有相似的体会—-对游戏的兴趣随着对系统的学习逐渐上升，到达顶点后又逐渐下降，因为随着对游戏的精通，挑战性慢慢地消失了。

有时候，简单的技术变得太过明显以至于破坏游戏其他部分的平衡。然而，通常罪魁祸首是脆弱的对手，因为AI不能体现某些核心游戏机制，因此不能为玩家提供强大的挑战。问题是，游戏设计师对玩家所做的承诺是AI程序员无法兑现的；前者所设想的游戏系统超过了现代游戏AI的能力范围。

对称游戏的灾难

并非所有游戏都会让玩家的感情经历Chick抛物线。许多游戏基本上是不对称的—-《超级马里奥兄弟》、《侠盗猎车手》、《魔兽世界》、《半条命》等等，它们的AI简直就是抑制玩家进步的减速器，可以轻易地提供合适程度的挑战。受到Chick抛物线现象影响最大的游戏是对称游戏—-电脑模拟人类玩游戏。

这些对称游戏，如《星际争霸》、《街头霸王》、《战神的挑战》、《光晕》等，都面临特殊的挑战：判断这些游戏的机制不能简单地根据它本身的优势，还要看看AI是否能理解选项并成功地执行它。不幸的是，许多有趣的游戏创意都达不到这个要求。

AI在处理信任和背叛、长期投入、正面战斗和避开对人类来说很明显的陷阱等方面表现恶劣，这是众所周知的。特别是信任问题，许多试图制作经典桌面游戏《外交》的可行单人版的努力就是败在这里；因为这要求游戏能够识别敌人、盟友和可能的盟友。

因此，为了避免Chick抛物线现象，对称游戏的设计师必须认真考虑各种游戏机制的应用。太过依赖AI的游戏短期内会让玩家觉得有趣，但随着玩家越来越了解系统，就会对游戏失去兴趣—-一旦玩家精通系统，他们便可以使用机制去围绕着AI运行。

当然，对称游戏的设计师通常会把游戏设计成多人模式，如《战地》系列或格斗游戏，这其实是选择牺牲单人模式的长寿换取多人模式的深度。如果我们假设游戏的资深玩家只对和其他玩家一起游戏感兴趣的话，非常规武器便很好

人类的大脑太灵活了，能够轻易地认出不同于游戏其他部分的异常机制。这对游戏来说有许多优势；可以通过角色升级彻底改变只有多人模式的游戏如《军团要塞2》，不必担心越来越弱的AI会崩溃。

AI设计

然而，对称单人游戏在AI方面的考虑必须与对人类玩家的考虑相当。即使很痛苦，为了照顾AI，设计师也必须放弃他们最中意—-通常是最有创意的想法。游戏设计是一系列得失权衡的过程，使AI强大起来是避免好感抛物线下降的关键。

尽管如此，有创意的开发者可以在设计阶段而不是交给AI程序员阶段就解决这个问题。使Chick对《帝国：全面战争》的兴趣下降的一个游戏机制是水陆两栖入侵。AI在入侵海域另一端的玩家时，不能够协调好它的陆军和海军，所以难以保证侵略的持续性和有效性。聪明的玩家会很快发现如果AI不能两路夹攻，那么平衡策略就太容易了。也许英国的陆军也没有那么可怕？

这个问题并非罕见；具有运输单位的策略游戏几乎总是在AI方面露出短板。同时同地协调陆地和海上单位以及必要的护卫舰，可不是一件容易的任务。

Big Huge Games的历史RTS《国家的崛起》采取了迟钝但还算有效的解决方法：到达海岸的陆军会直接变成船把自己送到海面上。到达目的地后，船会变成原来的陆军。这样就完全不必建造或管理运输船了。

这款游戏的设计师Brian Reynolds用这一种简单的方法解决了游戏中的经典AI难题，使水域地图对资深玩家保持吸引力。这种设计的缺陷可能牺牲了要求玩家建造运输船和其他海上单位的“现实主义”，但优点是，极大地延长了游戏的寿命。

此外，许多通过简单化支持AI的设计变化的副作用通常会让玩家觉得游戏本身更好玩。有相当多玩家并不怀念在《国家的崛起》中建造运输船。《文明3》和《文明4》分别引入全局单位支持和城市生产溢出；这两种变化都帮助AI管理它的资源，但也让普通玩家觉得游戏更加有趣，因为微操作的工作量大大减少了。

艰难的选择

当设计师必须放弃或简化确实有趣或核心的机制时，他就面临最严峻的挑战了。有时候，游戏可以成功地设置某些选择只允许玩家使用；在原版《文明》中，设计师Sid Meier在游戏后期引入核武器，但不允许AI使用。他的理由是，因为超级武器只出现在游戏后期，使用它们的玩家不可能滥用；这只是让他们感受最后一点疯狂的快乐。

此外，如果设计希望保留AI不可使用的机制，为了平衡AI的劣势，欺骗可不是一个可行的解决办法。允许太多仅人类玩家可用的系统会导致对称游戏变得不对称，进而影响策略的平衡。

在《帝国：全面战争》中，一旦玩家知道AI不能有效地发起两栖侵略，那么游戏局势就会立即发生改变。也许玩家不必在他们的海滨地区设防了？可能陆地同盟比海域同盟更重要？大概可以通过无效的侵略骗AI浪费资源？最重要的是，玩家不再扮演游戏中的国家元首了，他只是像知道AI不管用的玩家一样玩游戏—-这时的玩家就滑向好感抛物线的底部了。

最终，设计师们必须做出艰难的选择—-放弃心爱的机制或冒险减少重玩价值？除了纯粹的平衡，延长游戏寿命的选择确实存在且还不少，如给各种情境编写脚本、支持程序内容生成、允许MOD、开发资料片，等等。

然而，对于增加重玩价值，没有什么比增加电脑对手的策略性深度更重要的了。牺牲游戏的寿命为玩家换取一些短暂的乐趣，必然会从根基上破坏设计。正如Chick所说的，当玩家最终学会系统时，“那正是游戏应该起飞的时候。”学习的乐趣是确保游戏有趣的一个重要原因，但没有人会为了一个不存在的考验而学习。

（本文为游戏邦/gamerboom.com编译，拒绝任何不保留版权的转载，如需转载请联系：游戏邦）

GD Column 14: The Chick Parabola

by Tom Chick

On March 11, 2009 during the Three Moves Ahead strategy gaming podcast, freelance journalist Tom Chick introduce a phenomenon which has come to be known as the Chick Parabola:

My experience with Empire: Total War is this parabola of fondness. At first I don’t like it, so I’m at the bottom of the curve. I don’t like it because they do a terrible job with their documentation – it’s got a terrible manual; they want you to play through this scripted campaign if you want to learn anything; the tool-tips are really screwy. So, I’m hating it.

But then I’m playing it, and I’m learning it, and I’m liking it, so I’m climbing up that parabola. At the very top of the curve, I think, “Hey, I sort of figured it out. I like this game.” But then I start to discover that the AI is terrible, that it’s a dumb game, and I start coming down the far end of the parabola, and I am no longer fond of Empire: Total War.

Commonly, there’s this curve where I enjoy a game, and then I master the system, and then – unless it’s got a good AI – I lose all interest because I realize that mastering the system is where the challenge ends. Once I reach that point, the game is dead for me, and I hate that! That’s when the game should really start to take off.

Many veteran gamers will recognize this feeling from their own experiences – the rising enjoyment that comes from learning an interesting game system followed by an inevitable deflation as the challenge slowly disappears.

Sometimes, a simple technique or exploit becomes obvious that renders the rest of the game balance irrelevant. However, usually the culprit is a weak adversary as the artificial intelligence cannot grasp certain core game mechanics to offer the player a robust challenge. The problem is that the game’s designers have made promises on which the AI programmers cannot deliver; the former have envisioned game systems that are simply beyond the capabilities of modern game AI.

Symmetry Matters

Still, not all games suffer from the Chick Parabola. Many are so fundamentally assymetrical – Super Mario Bros., Grand Theft Auto, World of Warcraft, Half-Life – that the AI is simply a speed bump that can be easily tuned to provide the right level of challenge. The games which suffer the most are ones where the computer is forced to play the same game as the human.

These symmetrical games – StarCraft, Street Fighter, Puzzle Quest, Halo – have a unique challenge in that each game mechanic must not simply be judged on its own merits but also by asking whether the AI can reasonably understand the option and execute it successfully. Unfortunately, asking this question often disqualifies many interesting ideas.

Artificial intelligence is notoriously poor at handling issues of trust and betrayal, of long-term investments, of multi-front wars, and of avoiding traps obvious to any human. The question of trust, in particular, has torpedoed multiple attempts to make a viable single-player version of the classic board game Diplomacy, which relies so acutely on being able to read one’s enemies, one’s friends, and one’s supposed friends.

Thus, to avoid the Chick Parabola, designers of symmetrical games must weigh carefully the implications of various game mechanics. An interesting play option which over-taxes the AI runs the risk of making the game more interesting in the short-term – as the player learns the system – but less interesting in the long-term – once the player masters the system and can use the mechanic to run rings around the artificial intelligence.

Of course, designers of symmetrical games built primarily for multi-player – such as the Battlefield series or the fighting genre – can choose to sacrifice single-player longevity for multi-player depth. Non-conventional weapons are fine if we assume that veterans of the game are only interested in playing the game with each other.

The human brain is remarkably flexible, with the ability to easily process novel mechanics which are orthogonal to the rest of the game. This approach has many advantages; Valve has been able to radically change the multi-player-only Team Fortress 2 with each character update (giving the Demoman a sword and shield, for example) without having to worry about toppling over an increasingly rickety AI.

Designing for the AI

However, symmetrical single-player games need to be designed as much for the artificial intelligence as for the humans themselves. Even if painful, designers must be willing to leave some of their most orthogonal – and often most creative – ideas off the table for the sake of the AI. Game design is a series of trade-offs, and empowering the AI is important for avoiding the downward slope of the Parabola.

Nonetheless, creative developers can solve this problem at the design stage before it even reaches some doomed AI programmer. One game mechanic that pushed Chick over the edge with Empire: Total War was amphibious invasion. The AI was simply incapable of coordinating its land and naval forces together to launch a coherent and effective invasion of an overseas target. Smart players would quickly learn that if the AI could not attack amphibiously, then the strategic balance can be gamed easily. Maybe England’s troops are not such a threat after all?

This problem is not unusual; strategy games with transportation units almost always suffer from ineffective artificial intelligence. Coordinating land and naval units to be ready in the same place and at the same time – along with the necessary escort ships – is a non-trivial task.

Rise of Nations, Big Huge Games’s historical RTS, presented a blunt but effective solution to this problem; land forces which approach the shore simply turn into boats to carry themselves across the water. Once they reach their destination, the boats transform back into the original land units. No transportation ships ever needed to be built or managed at all.

With one simple stroke, Brian Reynolds, the game’s designer, removed a classic AI problem from the game, enabling water maps to remain interesting for veteran players. The design may have sacrificed the “realism” of requiring the player to build transport ships along with other naval units, but the upside was extending the game’s longevity significantly.

Furthermore, many design changes meant to bolster the AI by simplification often have the side effect of making the game itself more enjoyable for the player. Quite a few players did not miss having to build and herd transports in Rise of Nations. Civilization 3 and Civilization 4 introduced global unit support and city production overflows, respectively; both changes helped the AI manage its resources but also made the game more enjoyable for the average player by drastically reducing micromanagement.

Tough Choices

The designer’s biggest challenge comes when a mechanic which is demonstrably fun or core to the game’s theme needs to be simplified or dropped. Occasionally, a game can get away with assuming that a certain option will be human-only; in the original Civilization, Sid Meier added nukes to the end-game but didn’t allow the AI to use them. He reasoned that because the super-weapon came only at the end of a game with such scope, players who used them were not abusing the game; they were simply having a bit of crazy fun at the end.

Further, if the designer wants to maintain a mechanic that the AI can’t use, cheating is not a viable solution for balancing away the AI’s disadvantage. Allowing too many human-only systems effectively turns a symmetrical game into an asymmetrical one, which will eventually affect the strategic balance.

In the Empire: Total War example, once players know that the AI will never launch an effective amphibious invasion, the rest of the game changes immediately. Maybe players don’t need to bother defending their coastal territories? Maybe land-based allies are more important than water-based ones? Maybe the AI can be tricked into wasting its resources on futile invasions? Most importantly, the player is no longer playing like a queen – she is playing like a gamer who knows that the AI doesn’t work, one who is on the downhill side of the Parabola.

Ultimately, the designer may have to make a tough choice – drop a beloved mechanic or risk shortening the replayability? Many options do exist to extend a game’s longevity outside of pure balance – scripting a variety of scenarios, supporting procedural content generation, providing robust mod support, developing post-release content, and so on.

However, for robust replayability, nothing compares to pure strategic depth with a competent computer opponent. Sacrificing the game’s longevity to provide a few moments of fun for the human is essentially eroding the design at the foundation. As Chick puts it, when the player finally learns a system, “That’s when the game should really starts to take off.” The joy of learning is a big reason why games are fun, but no one wants to study for a test which doesn’t exist.(source:designer-notes)