Mini Metro 是关于在城市规划中设计地铁线路的策略模拟游戏。通过在站点之间连线让列车通过,还要随着新站点的建设和开放,不断调整线路。你需要利用有限的资源做出最好的设计。
用户评测:
最新:
特别好评 (119 篇评测) - 过去 30 天内的 119 篇用户评测中有 92% 为好评。
总体:
好评如潮 (3,699 篇评测) - 3,699 篇用户的游戏评测中有 96% 为好评。
发行日期: 2015年11月6日

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8月14日

Passenger AI improvements!

gamma26 build with AI improvements is available on the test branch.



Hey all,

We were hoping to have the gamma26 build tested and live before the Daily Deal today, but unfortunately what I thought was going to be just a few days improving the passenger AI turned into a couple of weeks. So business as usual. :)

We've worked our way through every bit of the decision-making code and found and fixed numerous small errors that would result in railcars leaving stations partially full or overfull, passengers making dubious decisions about which trains to board, passengers of the same shape making different decisions at the same station, and all sorts of other odd behaviour. It's gone through testing here, but I don't feel comfortable pushing it live just yet given it hasn't had any public testing. So if you're game, please switch to the test branch and give it go. If you think you've can see anything dodgy, please take a screenshot and send that and as detailed a description as possible to peter@dinopoloclub.com.

There are a couple of AI issues that I'd like to go over. The first is that in order to make the passenger decisions more consistent, we've had to remove the old hack that would encourage passengers to leave overcrowded stations immediately if a train was available, even if that train took a much slower route to their destination. The way we got those passengers to prioritise the longer route then had to have another hack to avoid them flip-flopping routes, so the whole system is much more robust with both those hacks gone. We're working on a replacement system to discourage passengers taking routes that involve waiting at overcrowded stations instead; this will have the same result as the old code, but it'll work much more elegantly with the AI's search algorithm.

The second issue is that we've found that high-risk connections can pose a real problem with the way passengers make decisions about which route to take. By high-risk I mean passengers deciding to take a route involving a tight transfer onto a different line to get to their ultimate destination. If they miss that transfer due to either an optimistic estimate of their original train's arrival time at the transfer station, or a pessimistic estimate of the connecting train's arrival time, then the cost is potentially very high. If the connecting train is the only train on its line, or if the line is very long, then the passenger will likely flip to a completely different path once it realises it won't make the connection. This can lead to passengers going back-and-forth as they try to catch different trains. We've done what we can to address this issue by building in a threshold for tight connections that goes up and up as the search algorithm tries to predict further and further into the future. For example, if we're predicting a transfer 30 seconds in the future, then the passenger has to predict it'll get to the station at least 3 seconds before the connecting train, otherwise it assumes it'll miss the train and cost that particular route accordingly. This is as much as we feel comfortable doing without either adding state to the passenger AI (at a cost of robustness), or improving the train location prediction (at a significant cost of development time, and no doubt introducing a litany of new bugs).

Ultimately this is a problem given the odd timescale the game runs at, with few railcars hitting stations infrequently, compared to actual metros that have many more cars with far greater frequency of station visits.

Anyway, I know this has been a little long-winded, so thanks for reading through! I figured some players would appreciate a peek behind the scenes of what is by-far the most complicated algorithm in Mini Metro.

Slight non-sequitur back to gamma26; we're aware of some rendering issues on the Linux build, (the in-game UI elements are flickering on our Ubuntu machine) so we have to at least get those resolved before pushing this build out to the default branch.

Keep those cities moving!

Peter
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6月19日

Elegant Engineering bundle

Want more games like Mini Metro?



You're in luck! We've partnered with the development teams behind Train Valley, Poly Bridge, Simple Planes, and Turmoil to bring you the Elegant Engineering bundle. All for a 40% discount off the individual prices!

http://store.steampowered.com/bundle/3474/Elegant_Engineering/
11 条留言 了解更多

评测

“Mini Metro makes mass transportation sublime”
83 – Kill Screen

“Très bon”
8 – Gamekult

“It's so satisfying that the moment one game ends ... you'll immediately want to start again”
Boing Boing

关于这款游戏

在 Mini Metro 中,你将肩负起在飞速发展的城市中涉及地铁的重要任务。城市最初只有三个地铁站,在此基础上,你需要建立新的站点,并在站点之间设计线路,让上下班的通勤者们在路上少花时间。每个站点能容纳的等车乘客数量是有限的,所以你的地铁网络必须设计精密,避免发生拥堵和旅行延误的情况。



城市在不断扩张的进程中,需要更多的站点,以帮助更多的通勤乘客。对地铁网络的要求也会越来越高。你需要经常重新规划线路,使运输效率最大化。你每周获得的新资源都对建设有所帮助,但你得决定如何分配。

大多数的地铁方案都会以失败告终。也许站点建设的太快了,也许大量乘客滞留在了站台上。你的地铁线路能维持多长时间运营呢?

主要功能

  • 游戏既紧张又轻松,既复杂又简单。这怎么可能呢?你自己来玩玩看就知道了。
  • 三种游戏模式:快速得分的正常模式、没有限制的无尽模式、挑战自我的极限模式。
  • 在 18 座全球知名城市中涉及地铁线路:伦敦、纽约、巴黎、柏林、墨尔本、香港、大阪、圣彼得堡、蒙特利尔、旧金山、圣保罗、首尔、华盛顿特区、开罗、伊斯坦布尔、上海、孟买、奥克兰。每座城市都有独特的主题、特定的困难以及当地的风格。
  • 城市发展具有随机性。每个游戏都不一样。上一个游戏中成功的战略在新的游戏中可能就没什么用了。
  • 每张地图都是大师之作,你可以达到伦敦地铁之父哈利·贝克那样的水准。你可随心所欲的调整地铁方案,还可把你的杰作作为电脑桌面!
  • 来自 Disasterpeace 的配乐
  • 提供夜间模式和色盲模式
  • 还有棒棒的列车呢!

游戏演示

你可在下方地址了解 Mini Metro 并试玩伦敦地图:游戏演示

系统需求

Windows
Mac OS X
SteamOS + Linux
    最低配置:
    • 操作系统: Windows XP, Vista, 7, 8 or later
    • 处理器: 2 GHz or faster processor
    • 内存: 1024 MB RAM
    • 图形: Shader Model 2.0
    • DirectX 版本: 9.0c
    • 存储空间: 需要 300 MB 可用空间
    最低配置:
    • 操作系统: OS X 10.7 Lion or later
    • 处理器: 2 GHz or faster processor
    • 内存: 1024 MB RAM
    • 图形: Shader Model 2.0
    • 存储空间: 需要 300 MB 可用空间
    最低配置:
    • 操作系统: Ubuntu 12.04 LTS or later
    • 处理器: 2 GHz or faster processor
    • 内存: 1024 MB RAM
    • 图形: Shader Model 2.0
    • 存储空间: 需要 300 MB 可用空间
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最新:
特别好评 (119 篇评测)
总体:
好评如潮 (3,699 篇评测)
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