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分析桌面游戏的选择反馈反应时间

发布时间:2014-01-17 17:18:30 Tags:,,,,

作者:Max Seidman

游戏的核心是关于反馈。当玩家做出选择时,它们就像是提供该选择质量反馈的系统。在《使命的召唤》中,选择可能是“我是否该开枪?”在《Magic》中,它可能是“我是否该攻击这只生物?不管在什么情况下,当做出决定后玩家将快速收到反馈。在前一个例子中,玩家将通过视觉效果(以及听觉效果)得知自己是否击中。而在后面的例子中,玩家的敌人将做出决定,告诉他攻击是否是个好主意。

关于不同类型选择的反馈回应时间也不同。在桌面游戏中,玩家可能会在同个回合中执行一个行动并获得反馈(例如大多数投标游戏便是这么做的)。玩家可能会在游戏中做出另外的选择,从而在游戏最后便会获得成功或失败形式的反馈(例如,在大多数引擎创建游戏中选择所追逐的策略)。我们将反馈发生在同一个回合中的选择称为战术选择,而将反馈出现在整体游戏中的选择称为策略选择。

选择反馈回应时间范围

游戏中的战术选择和策略选择都是呈现在一个范围中,其轴线是选择反馈回应时间。轴线本身如下:

choice-feedback response spectrum(from mostdangerousgamedesign)

choice-feedback response spectrum(from mostdangerousgamedesign)

左边是战术选择,而右边则是策略选择。这些轴线是分析游戏的有效工具。让我们着眼于《银河竞逐》的图表:

choice-feedback-response-spectrum(from-mostdangerousgamedesign)

choice-feedback-response-spectrum(from-mostdangerousgamedesign)

就像我在2周前提到的,《银河竞逐》带有能够控制游戏战术部分的机制(角色选择),还有一个单独的机制能够控制其策略选择(引擎创建)。这两套机制代表的是图上的两个盒子,有趣的是它们是完全独立的机制。将其与纸牌游戏《失落之城》的图表相比较:

choice-feedback response spectrum(from mostdangerousgamedesign)

choice-feedback response spectrum(from mostdangerousgamedesign)

《失落之城》带有许多战术选择和一些策略选择,但它们都是源自唯一的一套机制!

现在这一范围便能够有效地分析一些桌面游戏,但实际上还不够。我们还未解释的一点是一刹那的反馈(即时满足)。还有一个是比一款游戏还久的反馈,例如在《Magic:the Gathering》比赛中选择桥牌的元游戏分析。以下是包括这些反馈的范围:

choice-feedback response spectrum(from mostdangerousgamedesign)

choice-feedback response spectrum(from mostdangerousgamedesign)

这能用于分析更广泛的游戏子集。例如,以下是使用这一框架(因为我并不了解棒球,所以大多数都是推测的)对于棒球的简要分析:

choice-feedback response spectrum(from mostdangerousgamedesign)

choice-feedback response spectrum(from mostdangerousgamedesign)

那又怎么样?

我希望的是除了用于分析个体游戏,这一范围也能够分析更广泛的游戏类型。就像我们所看到的,体育游戏和电子竞技更倾向于全范围游戏。我们习惯于专注战术和策略的桌面游戏,并未特别延伸到元策略中。我们经常期待电子游戏能够专注于调整与战术选择,而未特别延伸到策略中。

choice-feedback response spectrum(from mostdangerousgamedesign)

choice-feedback response spectrum(from mostdangerousgamedesign)

如今,电子游戏显然包含了元策略,有时候桌面游戏也带有调整策略,而电子游戏专注于调整而桌面游戏专注于策略则是许多游戏所遵循的强大惯例。这能够帮助作为设计师的我们从更大的范围去理解游戏。过去我写过有关“默认动作”(游戏邦注:不要求玩家在回合中做出策略行动)如何帮助休闲桌面游戏玩家处理策略桌面游戏的内容。我之所以会这么建议是因为许多人并不想要做出策略选择,包括许多电子游戏玩家。这也是为什么电子游戏不会包含许多策略或元策略的原因(当与桌面游戏所包含的策略数相比较时)。

理解这点能够帮助设计师更好地理解用户的交集。例如,我发现许多桌面玩家朋友也很喜欢rogue数字游戏。我们可以通过理解桌面游戏的策略与惯例而解释这种情况;在范围中,比起电子游戏,rogue游戏更像是原型桌面游戏。rogue游戏也倾向于遵守其它桌面游戏的惯例,就像基于回合制之类。我并不是想说rogue游戏是桌面游戏。拥有框架能够帮助设计师更好地谈论游戏惯例并有意识地操作它们。当非数字游戏变得越来越数字化时,将电子游戏惯例移植到桌面游戏(反之亦然)将变得更有价值。

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

Choice-Feedback Response Time

by Max Seidman

At their core, games are about feedback.  They are systems in which, when a player makes a choice, the system gives feedback as to the quality of that choice.  In Call of Duty, that choice might be “Do I fire my gun or not?”  In Magic, it might be “Do I attack with this creature or not?”  In either case, after making the decision the player receives fairly quick feedback.  In the former case, the game shows her visually (and also aurally) whether or not she hit.  In the latter case, the player’s opponent makes a decision and show her whether or not attacking was a good idea.

The response time for feedback varies between differing types of choice.  In a board game, a player might perform an action and get feedback on that action within the same turn (for example, most bidding games work like this).  There might be another choice she makes about which she gets feedback at the end of the game in the form of victory or defeat (for example, choosing which strategy to pursue in most engine building games).  If this is starting to sound familiar it should, as I wrote about it three weeks ago in my post about tactics and strategy; we call a choice for which feedback happens within the same turn a tactical choice, and we call a choice for which feedback takes a whole game a strategic choice.

The Choice-Feedback Response Time Spectrum

Tactical and strategic choices in a game can be show on an a spectrum where the axis is choice-feedback response time.  Here’s what the axis itself might look like

On the left are tactical choices (for which feedback is given within the turn), and on the right are strategic choices (for which feedback is given at the end of the game).  These axes can be a useful tool for analyzing games.  Take a look, for example, at Race for the Galaxy’s graph:

As I mentioned two weeks ago, RftG has a mechanic that governs the tactical portion of the game (role selection), and a separate mechanic that governs its strategic aspect (engine building).  These two sets of mechanics are represented by the boxes on the graph, and it’s interesting to note that they are completely separate sets of mechanics.  Compare that to the graph for the Lost Cities card game:

Lost Cities has lots of tactical choice and some strategic choice, but they are all provided for by a single set of mechanics!

Now this spectrum is pretty useful for analyzing some board games, but it’s actually really narrow.  One thing that isn’t accounted for is split second feedback (instant gratification).  Another is feedback that takes longer than a single game, for example metagame analysis in choosing what deck to play in a Magic: the Gathering tournament.  Here’s what the spectrum might look like including those two on the ends:

This is useful for analyzing a broader subset of games.  For example, here’s a brief analysis of baseball using this framework (note that I know next to nothing about baseball, so most of this is conjecture):

So What?

Where I’m going with this is that in addition to being used for analysis of individual games, this spectrum is also useful for analyzing broader types of games.  As we’ve already seen, sports and e-sports tend to be full spectrum games.  We’re used to board games focusing on tactics and strategy, not uncommonly stretching into metastrategy.  We usually expect video games to focus on twitch and tactical choices, not uncommonly stretching into strategy.

Now, video games can obviously contain metastrategy, and board games can sometimes have twitch choices, but video games focusing on twitch and board games focusing on strategy is one powerful convention that many games conform to.  This can help us as designers understand  games at a broader level.  In the past I’ve written about how “default actions” (not requiring players to make strategic actions on their turns) help casual board game players handle strategy board games.  I propose that this is because many people aren’t interested or equipped to make strategic choices, including many video game players.  And this is why video games tend not to include much strategy or metastrategy (when compared to the amount that board games include).

Understanding this allows designers to better understand intersections of audiences.  For example, I’ve found that many of my board gamer friends also enjoy rogue-like digital games.  This can be explained, in part, by this understanding of strategy and conventions of board games; on the spectrum, rogue-likes look much more like prototypical board games than video games.  Rogue-likes also tend to conform to other board game conventions, like being turn-based.  I’m not trying to say that rogue-like games are board games.  It’s simply useful for designers to have a framework to talk about game conventions and manipulate them consciously.  As nondigital games become more and more digital, being able to experiment with porting video game conventions to board games (and vice versa) is going to be extremely valuable.(source:mostdangerousgamedesign)


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