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关于《生化奇兵3》的AI同伴Elizabeth的相关设想(下)

发布时间:2011-05-03 00:14:04 Tags:,,,,

游戏邦注:本文作者Taekwan Kim以《生化奇兵3:无限》中Elizabeth为研究案例,针对游戏中的AI同伴设计展开探索性猜想。全文分为上下两篇,此为下篇内容。

在本文的上篇,我们以Elizabeth为研究案例,针对游戏AI同伴的设计做了一番猜测。为了突出《生化奇兵3:无限》设计原理中的有利于玩家的卓越部分,我们在下篇中将继续以为其例,结合其他一些已知的游戏技术,做一个拓展性猜测。

我们会先论述一些在上篇中提出的关注点,然后从游戏设计和玩家体验的观点出发,挖掘出过去的游戏AI同伴并不那么成功的根源。

bioshock-infinite-preview-screenshots

bioshock-infinite-preview-screenshots

心心相映和独立自主

在上篇中描述的自我拓展其实根本不是关于自我,这也许会让玩家有些意想不到。如果说有人只是在游戏中晃悠就得到所谓的“自我拓展”,那他也不需要同伴了(所以就有了自以为“超脱”于同伴关系的人了)。要解决先前已讨论的问题,AI同伴的自主性和独立性就是必不可少的,因此任何设计方案都必须至少能保证这个设想。

如果AI同伴只是一个任务代理人,或附加在真实玩家技能上的模拟图层,那也用不着大费周章了,因为到头来还是玩家自己动手,搞定一切事情。这就是为什么Laurie Cheer的Tyrant Guard让人大感失望,归结原因就是AI同伴没有恰当地响应玩家的行动——一个独立性缺失的反例,即一个执行不完全的代理人和其不可预见性夺走了玩家做出恰当反应和特定反应的能力。

这个关键可能是与直觉相悖的想法,即展现同伴的独立不一定取决于不可预见性。毕竟,同伴关系中的不可预见性的目标只是,通过先强调那些出乎意料或未知的自我拓展的方法,然后证实同伴的价值。实际上,我们并非想让同伴行动真的不可预测。就感知智能来说,我们甚至可能会说就像AI敌人的不可预测性一样,AI同伴的行动应该能被玩家所预测。从确认偏误(游戏邦注:确认偏误意指人们以符合自己目前想法的方式来搜寻或解读资讯的倾向,进而导致决策受到影响并且妨碍了学习)的研究中得知,我们往往会为了证明已存在的臆测而歪曲自己的的研究。我们自己牵涉其中,因为我们寻找自己重视的东西,也就是,我们希望AI敌人具有不可预测性,同时AI同伴又存在可预测性。

大部分情况下,一个不那么可预测的AI敌人就拥有模仿适应能力,这意味着玩家不可能在它们身上故伎重施。无论如何,玩家会聪明地应对不同形势,这意味着当AI同伴配合玩家的行动时(当然玩家对同伴的行动期望是肯定的),AI同伴的“适应能力”和智能就被玩家感知到了(这甚至发生在多人游戏模式中,在这种模式中,不能达到期望的人被认为缺乏技术)

总体来说就是,我们真正想要的不是完全意义上的自主(独立于外部系统的影响),而是相应的一致性。这个技巧是为了达到信赖而不是依赖。

我们的首要需求是,一种让玩家和同伴地位平等的关系,这种关系中不存在第二等或最高等(Irrational强调这一点,所以Elizabeth被选为研究案例)。例如,如果Elizabeth总是并且只是充当玩家DPS时的CC,那就太无趣了,甚至是无聊透顶,这种情形恰是真正意义上的“可测”的游戏设置。

游戏操作风格和行为边界

不幸的是,所谓的“平等”与玩家的习惯和操作风格大有关系。我们真正需要的是让AI同伴根据玩家的意图进行主动模仿。我们希望同伴会独立行事,因为这样才能与玩家的行动配合得天衣无缝。

换个角度想,如果这个同伴总是等着玩家先行动(通常情况是如此),那么,玩家幻想同伴能有点自主性实在是异想天开。我们需要的是能向同伴传达自己的意图,而不是对同伴发号施令,这样才能使同伴自发自主地行动。

这种设想的真正目标是允许玩家快速感知bot的行动范围来防止玩家角色受冷落。然后在这个行动范围内,bot就能自由行动。如此,一旦我们拥有了合适的分工(稍后讨论),玩家对bot的行为应该了如指掌,同时也达到了所谓的“平等”。

让我们来考虑下范例的实施。太过简化的信息传达的方式大约可以称为“阵式”,这是玩家得以维持不同阵式来表现操作风格。以下是两个常见的FPS游戏操作风格,可作为说明这种阵式或模式的根据:

速度型玩家

这类玩家急不可耐地赶往下一个目的地。花更少的时间杀变异人,以节省更多抢占地盘的时间。维持生命值的方法就是尽快赶赴下一个安全区,注重保存不断减少的资源。

谨慎型玩家

这类玩家从容不迫地前进。他们得在安全无虞的环境中维持生命值,因此其游戏进度被当成次要任务,用最少的资源代价来造成最大的伤害输出才是重点。至于返回去拿暂时用不着的物品根本不是他们所顾虑的问题。

任务的传达对玩家来说并不是什么问题,他们已从检查武器和使用的技能,到测算与变异人的距离和确定邻近范围内变异人的数量等一系列过程了解到任务内容。玩家反而需要估计的是代理任务的方方面面,他们最重视和享受的就是在代理任务里施展这种游戏操作风格,这样玩家们可以防止敌人的侵犯和不必要的重复操作。

所以就代理Elizabeth而言,这些游戏操作风格意味着什么?这意味着当Elizabeth带领玩家、承受比玩家本身更多或相同的伤害时,迅度型玩家更可能对此感觉良好。这也意味着Elizabeth应该迅速从紧迫的变异人堆里突围,即使变异人还活着。这还意味着Elizabeth的攻击范围的扩大、高杀伤性技能的释放和能源的使用可能不受限制。

然而,谨慎型的玩家却更乐意亲自解决敌人的密集来袭,所以他们希望Elizabeth站远点,少用点杀伤技能,多加点被动技能,最主要的是还要专注于长远的、可持续的伤害。

我们可以再进一步设想,例如把Elizabeth受到的伤害转移到速度型玩家身上,而增加谨慎型玩家的伤害输出(以减少Elizabeth的伤害输出)等等。如此,我们就在玩家和AI同伴的分工方面更深入了。

总之,在保持可预测性和防止竞争型代理的同时,这种用行为边界而不是行为专一的方案为AI同伴保留了更多的行动余地(“自主”)。最后,通过分工,我们进一步增强可预测性和合作型代理。

玩家促进任务分工

最后我们谈谈玩家和AI同伴之间的分工。不妨回顾一下,分工的重点是促进玩家的自我拓展。单纯地赋予Elizabeth那些玩家没有的技能,似乎达到了理想效果。但实际上,这种方案会造成Elizabeth和玩家之间的疏离,因为Elizabeth的能力看似太过专横随意,且与玩家的技能建设不太相干。再者,自我拓展是“共同雕刻”的过程,这种方案显然又与这个过程脱节。我们仍然希望那些玩家得不到的技能,能以某些方式在玩家技能建设之外发展起来。

一个算不上新颖的解决办法是,让Elizabeth获得的技能根据玩家最常使用的能力和武器来决定的,并且与玩家在代理任务中的支出而获得的东西也有关系。

如果玩家造成50的近程伤害,Elizabeth就获得寒冬爆发(《生化奇兵3:无限》中的一种技能)。50以上的近战伤害可使寒冬爆发形成一个持续的、遍及全体的惰性光环,它可使接近的移动物体减速。50以上的近战伤害还可以产生伤害抗性、或扩大光环等状态。(如果变异人数量有限,这大约也增加了缩小/扩大和计划/思考游戏的乐趣)。在不同的游戏进程里,她也可以形成时间操纵技能,或者其他辅助近战玩法的技能。

如果我们给不同的变异人不同的免疫力和抗性,那么切换DPS到Elizabeth身上就会更自然。这样,玩家使用的辅助技能也能暂时增加Elizabeth培养的伤害类型。

但我们还可以进一步拓展。比如,玩家能获得的所有精力可以长期供应给Elizabeth(限制玩家角色,使Elizabeth生效)。这样,Elizabeth就不需要自己获取能量,但她却可以用这些精力来

增强和培养她自己的技能。我们甚至可以把这种精力转移拓展到弹药、武器、生命值甚至是eve能量,等等。这种简易的精力转移可以为玩家带来持久有效的光环(类比《黎明战争2》的物品捐赠)。

以上方案使得Elizabeth成为玩家的一个游戏投资点,此外,还可以促进玩家与AI同伴的情感关系和鼓励二者合作奉献。

但以上方案的真正优势在于,所有得到和产生的东西是作为玩家常规玩法和技能建设的延伸或结果。这就促进了游戏平衡,缓和了“Fatman problem”现象所带来的问题,解决了Ken Levine

所提出的“锤子和钉子”问题(即“当你有一把锤子,一切看起来都像是钉子”,玩家可以只靠闪电和霰弹枪就解决《生化奇兵》所有的挑战,意指太过简单地解决所有问题)。通过增加特殊化的意义和可玩性,建立充许施加辅助增效技能的框架结构,来鼓励玩家同时发展多重技能。

结论

从设计的观点出发,冒出模糊的概念,盼望设计程序,最后幻想成真,这些都很简单,但作者肯定在他自己看不到的环节上仍存在不少难题。除此之外,本文中提出的解决方案也可能产生其自身的设计问题。

一个谨慎惯了的玩家不可能经常地自动变成速度型玩家,且为了防止游戏过程中被搁置和无效的分工进程,所以我们需要提供奖励或者设计挑战来鼓励玩家改变操作模式。

另外在向玩家传达清楚的行为边界中,“谨慎”或“迅速”的客观属性限制了各自的价值(即使分工能解决这个问题)。游戏操作风格和任务之间的概念界线至多是模糊的,所以我们还需要避免落入思维陷阱,即假设某种姿态总能通过使用某种技能或武器达到。这些与Elizabeth的设计相关的观点,还需要经过含广泛抽样调查的游戏测试来证实。

无论如何,此番讨论的主要目标是推进关于AI同伴发挥极限功能的假想。我们还没看到大量游戏中能出现与玩家一样强大和重要的AI同伴,所以很期待Irrational即将推出的新作能带给我们什么样的惊喜。

凭借我们现在所设想的AI技术,我们真的能够实现那种多人游戏模式下的游戏体验吗?作者相信答案是肯定的。(本文为游戏邦/gamerboom.com编译,转载请注明来源:游戏邦)

Thinking About Elizabeth: Part 2

This is a continuation of last week’s exploration of fully AI controlled companion design. Once again, it’s really more of a general discussion, but BioShock Infinite was chosen as a hypothetical case study in order to highlight certain salient aspects of its design philosophy which work to our advantage, and to utilize these, along with some of the known mechanics, as starting points for extrapolation.

Anyway, let’s address some of the concerns that were brought up in the comments of the last post, and attempt to root out why fully AI controlled companions in the past haven’t been all that successful from a design/player experience point of view.

Perception and Independence

Perhaps unexpectedly, self-expansion as described in the last post is actually about things fundamentally not of the self. If one could simply go out and get those things, one wouldn’t need a partner for expansion (hence we have individuals who feel they have “outgrown” a relationship). It is therefore essential that any design solutions to the problems previously discussed need to keep up at least an illusion of autonomy and independence for the companion.

If the AI companion is merely a proxy or artificial layer added to de facto player controlled abilities, that’s just not going to do the job, because in the end it is still the player doing everything that matters. This is why Laurie Cheers’ example with the Tyrant Guard feels frustrating, because it really boils down to player controlled abilities not properly responding to player action—a case of reverse lack of independence where an incompletely implemented proxy and unpredictability strips the player of his ability to respond properly and intentionally.

The key, perhaps, is the counter-intuitive idea that the appearance of independence in a partner doesn’t have to rely on unpredictability. After all, the purpose of unpredictability in a partnership is simply to pleasantly validate the partnership’s value by highlighting formerly unexpected or unknown avenues for self-expansion. We don’t actually want our partners to be truly unpredictable.

In terms of perceived intelligence, we might even go as far as to say that companion AI should be as predictable as enemy AI should be unpredictable. We know from the wealth of research on confirmation bias that we tend to skew our search for evidence to confirm our already existing hypotheses. This is relevant to us in that, because we look for what we value, whereas we look for unpredictability in enemy AI, we look for predictability in companion AI.

For the most part, a slightly unpredictable enemy AI simulates adaptability and implies that the same trick won’t work every time. With companion AI, however, we can already expect that the player will react intelligently to the situation. Which means “adaptability” and intelligence is perceived when the AI predictably corresponds with player action—when the player’s expectations for the companion are confirmed (this even happens in multiplayer, where failure to meet expectations is perceived as lack of skill).

The whole point of this is that what we want isn’t really autonomy in the full sense of the word (independence from the influence of outside systems), but proportional correspondence. The trick is to achieve reliability without falling into dependency.

A primary requirement for us, then, is a partnership in which both the player and the companion have equal footing, where neither is secondary nor mostly superfluous (Irrational’s emphasis on this was why this example was chosen to begin with). For instance, if Elizabeth is always and only playing CC to the player’s DPS, that’s boring—and worse, exactly the situation that is really meant by “predictable” gameplay.

Playstyle as Behavior Boundary

Unfortunately, what is perceived as “equal” is highly relative to the pace and playstyle of the player. What we really need, then, is a way to simulate initiative taking based on player intention. We want a companion that does something autonomously because it’s the most obvious and natural fit for what the player is trying to do.

Let’s think about this another way. If the companion is always waiting for the player to act/move first (the usual solution), it’s pretty much impossible to even attempt an illusion of autonomy. So we need to be able to tell the companion what the player is trying to do, not what the companion should do, so that what the companion should do arises organically and of its own accord.

The real goal here is to allow the player to quickly communicate acceptable parameters of bot behavior to prevent the player from being overshadowed. We are then much freer to allow the bot to run mostly unhindered within those parameters. Then, once we have proper job division (to be discussed later), everything the bot can do should fall nicely within player expectations, as well as feel “equal”.

Let’s consider an example implementation. A simplistic way to communicate the necessary information might be something like “stances”, where the player can sustain difference stance modes to indicate styles of play (to draw “acceptable parameters” from). Here are two common FPS playstyles that might suitably serve as bases for these declarative stances or modes:

1. Expeditious

An expeditious player is in a hurry to get to where he wants to go. He spends less time killing mobs and more time focusing on gaining ground. The way to preserve health is to get to the next safest location as effectively as possible. Concern for conserving resources is therefore minimal.

2. Meticulous

A meticulous player wants to take his time moving forward. His health preservation relies on insuring there are no surprises, and that one’s flank is fully clear.

Making headway, therefore, takes a far backseat to dealing maximum damage with minimum resource expenditure. There are no qualms here about backtracking in order to pick up something which the player didn’t need earlier.

Importantly, communicating the job the player wants to fulfill is not really the issue here. We can already do this by looking at the weapon or skill the player is using, his proximity to mobs, and the number of mobs within that proximity. Instead, we need to assess the aspects of the player’s agency that the player values and enjoys exercising the most with these styles so that we can prevent encroachment or unnecessary overlap.

So, what do these styles mean in terms of Elizabeth’s agency? A player in expeditious mode is more likely to be fine with Elizabeth running ahead of the player and dealing damage in amounts greater than or equal to the player. It also means Elizabeth should be quick to disengage mobs outside a relatively tight radius, even if the mob is still alive1. Elizabeth can be looser with area of effect and high damage skills, and less conservative of resources.

A player in meticulous mode, however, takes great pleasure in dealing high amounts of damage himself. So we want Elizabeth to stay mostly behind the player, use less damage skills and more utility or passive skills, and mostly concentrate on long distance, resource conservative damage. Abilities that manipulate time, snare enemies, avoid adds, decrease enemy damage resistance, etc.

We can then venture a bit into job division territory and add a little tactical depth by introducing passive attributes to stances, such as damage transference from Elizabeth to the player in expeditious mode and increased damage output from the player (at the cost of decreased damage output from Elizabeth) in meticulous mode. Etc.

Anyway, the point is that such schemes that use behavior boundaries as opposed to behavior specificities allow far more leeway (“autonomy”) while maintaining predictability as well as preventing competing agency. Lastly, we can increase predictability and cooperative agency further through job division.

Player Driven Job Division

Ok, let’s finally talk about job division. Recall that the whole point of job division was to help facilitate the feeling of self-expansion. It would seem, then, that

simply giving Elizabeth stuff the player doesn’t have access to should do the trick. In effect, however, such a scheme would create distance between Elizabeth and the player because her abilities would seem arbitrary and unrelated to the player’s build. Again, self-expansion is about “mutual sculpting.” We still want stuff the player can’t have, but we need them to develop out of the player’s build in some way.

There’s no need to get too cute with this though—a less than original solution is just to have Elizabeth gain abilities based on which types of abilities/weapons the player uses most frequently. This also has the effect of making them something the player earns over time through agency expenditure.

If the player makes 50 melee kills, Elizabeth gets winter blast. 50 more melee kills makes winter blast a constant, party-wide passive aura that slows down approaching mobs. 50 more gives damage resistance, widens the aura, etc. etc. This sort of thing. (Presumably, if mobs are limited, this also supports the fun of min/maxing and planned/deliberate gaming.) On a different playthrough, she might develop time manipulation abilities instead, or other abilities that help melee style play.

If we then give different mob types different immunities and resistances, we can make it more natural to switch off DPS to Elizabeth. Then, the support skills the player uses also push which damage types Elizabeth develops over time.

But we can take this further. Say that all vigors which the player comes into access to can be permanently sacrificed to Elizabeth (restricting one’s role to empower another). Elizabeth doesn’t have to gain the powers herself, but she might use them to augment or develop her own abilities. We might even extend this to ammo, weapons, health/eve items, etc. where parsimonious play will lead to significant permanent buffs for the player (cf. Dawn of War II item donation).

The above schemes allow Elizabeth to become an investment sink, and the later additionally promotes the emotional connection cooperative sacrifice encourages.

Together, they would help maintain the illusion of self-expansion far beyond the point of diminishing returns.

But the real advantage here is that everything is earned and arises as an extension or result of the player’s regular play and build. This facilitates game balance, alleviates the “Fatman problem”, and helps mitigate the “when you have a hammer, everything looks like a nail” problem described by Mr. Ken Levine (players would literally solve the entirety of BioShock using only electro bolt and shotgun) by making specialization meaningful and fun again, and by establishing a framework from which we can permit synergistic passive bonuses to encourage the development of multiple abilities in parallel.

Conclusion

It’s easy to come from a design point of view and spout out vague concepts expecting programming to just make it happen, and I’m completely certain there have got to be difficulties in that department which I haven’t been able to see. But beyond those, there are still certain design problems which the “solutions” proposed in this post might cause themselves.

A naturally meticulous player, for example, is unlikely to voluntarily switch out to expeditious all that often, so we need to give incentives or design challenges in ways that encourage mode changes in order to prevent a job division progression that becomes pigeonholed and unworkable towards the end of the game.

Plus, the subjective nature of “meticulous” or “expeditious” limits their value in communicating to the player explicit behavioral boundaries (although job division helps out with that). The conceptual line between playstyle and job is nebulous at best, so we also need to avoid falling into the thought trap of assuming that certain stances will always be played using certain skills/weapons. These points make designing correlate behaviors for Elizabeth require extensive playtesting with a wide sampling pool.

But at any rate, the main goal with this discussion was to push our assumptions about the limits of AI companions. We haven’t seen many (any?) games which give fully AI controlled companions as much power and importance as the player, so I’m looking forward to how Irrational is going to tackle that with their forthcoming game.

So, can we really achieve the feel of multiplayer co-op with the AI technology we have right now? I believe the answer is a definite yes.(source: gamasutra


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