Co-op Case Studies: Star Trek – Expeditions

Reiner Knizia is best known in the co-op field for Lord of the Rings (2000), the game that kicked off the co-op revolution of the ’00s and ’10s. However, he also produced a second co-op game a decade later, Star Trek: Expeditions. (As with the Lord of the Rings case study, we at one time had this case study in Meeples Together itself, but when the game didn’t gain the same renown as Lord of the Rings, we decided to replace it with one of the hotter new games.)

This article originally appeared in the Meeples Together blog.


Star Trek: Expeditions by Reiner Knizia

Publisher: WizKids (2011)
Cooperative Style: True Cooperative
Play Style: Action, Card Management, Exploration

Overview

Taking on the roles of major characters from the rebooted Star Trek (2009) movie, the players explore a planet with the goal of eventually revealing nine “Captain’s Logs” — which together detail a set of tasks required to resolve political, rebel, and ecological problems on the planet.

In order to solve the problems laid out by the Logs, the players must succeed at a series of skill tests. Meanwhile, the Stardate keeps advancing and a Klingon battle cruiser menaces the Enterprise in the skies above. Continue reading

Making the Dick Move

Hollywood Blockbuster CoverWe were attending the last party in Hollywood Blockbuster (2006). That’s the Reiner Knizia game of auctions and moviemaking that’s also called Traumfabrik (2000) and Dream Factory (2009) because name changes sell games. I’d finished all my movies except one, and I hadn’t started that last one, so I had no use for any of the resources being offered.

Two players were going after me, and I glanced at each of their movie boards. One had a movie that was nowhere close to completion, but the other needed just a single audio effect to finish a film. I grabbed the only audio effect chit at the party, then tossed it to the side, unused.

That was the dick move. Continue reading

Psychology of Gaming: Loss Aversion

Game design can be influenced by many different fields. Among them, psychology is one of the most interesting, because it suggests ways that players might act that don’t necessarily go hand in hand with the actual mechanics presented in a game. Thus this week I’m kicking off the start of what I hope will become a series on psychology, with a look at loss aversion and gaming.


I found one of the best discussions of loss aversion at Usabilia, which describes loss aversion thus:

Loss aversion is a human characteristic that describes how people are intrinsically afraid of losses. When compared against each other people dislike losing more than they like winning. Thus losses loom larger than gains even though the value in monetary terms may be identical.

There isn’t much question on the existence of loss aversion. Instead, the modern scientific articles on the topic tend to focus more on why it occurs and what its boundaries on. I think some of those issues could be intriguing for a follow-up article, but for the moment I want to concentrate on the core of loss aversion as it applies to game design.

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The Alea Analysis, Part One: Ra (#1), Chinatown (#2), Taj Mahal (#3)

Over the course of 2009, I deliberately played through all 22 games then published by Alea, from Reiner Knizia’s Ra to the brand-new Alea Iacta Est. As I played each game, I wrote an analysis of it at my livejournal. If you wish, you can still read the original 22 Alea posts there.

Rather than keep all that material locked up on a non-gaming site, I’ve decided to bring it over here, where I’ll be revising and regularizing the content to make it into a more coherent series. So, here is the first of several articles on Alea, based on my thoughts from a couple of years back. I’ll be publishing more every 2 or 4 weeks, so as not to dominate the blog with this material. Continue reading

Game Decisions & AI: A Look at Modern Art: The Card Game

The last two years have been a programming whirlwind for me at my real-life job, Skotos. And that’s a segue into the fact that I just released my fifth iPhone eurogame conversion in 17 months. This time around, it’s Reiner Knizia’s Modern Art: The Card Game, the cardplay variant of his older Modern Art auction game.

I’ve written a bit about the development of each of my five iDevice games. You can find past article about Reiner Knizia’s Moneyabout Reiner Knizia’s High Societyabout Reiner Knizia’s Kingdoms, and about Michael Schacht’s Gold!

One topic that I keep returning to in these articles is that of artificial intelligences, or AI — the algorithms that make strategic decisions for the computer players in my card games. When I finished Money I said that I learned that abstract seat-of-your-pants decisions worked as well as calculations did. Then when I discussed High Society I talked about all the exacting calculations I built into my AIs. When I completed Gold! I acknowledged that AIs were different for each game … and that’s the impressions that’s likely to stay with me.

Modern Art: The Card Game made me appreciate the huge multitude of decisions that players make even when playing what seems like a pretty simple game. So that’s what I’m going to talk about today: how Modern Art: The Card Game works; how my AI for it works; and what that all reveals about the game’s design.
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Reiner Knizia’s Amun-Re: Still Innovative after All These Years

Though the Cult of the New ever dominates eurogame play, I increasingly find myself returning to the classics at least once or twice each month. That’s what brought me back to Reiner Knizia’s Amun-Re a few weeks ago.

I’ve always liked the game — with its combination of bidding and resource management — but during my last play I was really struck by how well Knizia has designed the game’s auctions.

So, I wanted to talk about that briefly this week, to highlight what I think is some cool game design that I’d love to see more of.

The Province Auction

The heart of the game is the province auction, where the players bid on the a number of provinces until each player is the sole winner of one of them.

Here’s some of the stuff that I think really works in the auction:
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Co-Op Interviews: Reiner Knizia — Lord of the Rings

In previous articles in this column I discussed the primordial co-operative play board games, from 1987 to 2000 — starting with Arkham Horror and ending with Lord of the Rings — and I talked with Richard Launius, who helped to kick-off the co-operative game explosion for the late 1980s.


This week I’m talking with Dr. Reiner Knizia, one of the top designers of Eurogames, and possibly the best known board game designer in the world. Just like Richard Launius, he’s a foundational co-op designer, because he’s the guy that got co-ops going again over the last decade, after they’d gone moribund for almost as long.

By chance, Knizia’s Lord of the Rings has just been rereleased by publisher Fantasy Flight in a new Silver Line Edition, which means it’s smaller and cheaper.

With that said, let me offer special thanks to Dr. Knizia for chatting with me about co-op games, as he rarely grants print interviews of this sort.
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Sweating the Details for iPhone Card Games: Visuals, AIs, and Player Numbers

This week Apple released my fourth eurogame iPhone release, Michael Schacht’s Gold!. It was a particularly exciting release for me not just because it was my first chance to work with Michael Schacht, but also because it was the first-ever (as far as I know) simultaneous release of a professional print game and an iPhone adaptation. Michael revealed abacusspiele’s edition of Gold! to fans at the Nuremberg Toy Fair on the same day that the iPhone edition became available in Apple’s iTunes stores.

To commemorate that release, and talk some more about the lessons learned in iPhone game designed, I’ve put together this article, discussing some of the more careful details that I had to consider when creating my newest game. If you’d like to see some of my other discussions of iPhone game design, I’ll point you toward Turning Reiner Knizia’s Money into an iPhone GameMaking Computers Think Like Auction Players (which I wrote for the release of Reiner Knizia’s High Society), and What Makes a Great Mobile EuroGame (which I wrote for the release of Reiner Knizia’s Kingdoms).
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What Makes a Great MobileEuroGame?

This Sunday my game company, Skotos Tech, released its third mobile game for the iPhone, iPod Touch, and iPad: Reiner Knizia’s Kingdoms. It follows on the heels of our previous releases, Reiner Knizia’s High Society and Reiner Knizia’s Money. All told, I’ve spent some goodly portion of my last year’s work on these three games (and the MobileEuroGame toolkit I’ve been creating, which is making it easier and easier to create new games as I go along). Along the way I’ve learned some useful lessons about choosing which games to adapt to mobile devices, and I’ve decided to talk about that this week.

For me, it’s a contrast between Reiner Knizia’s Kingdoms and Reiner Knizia’s Money — both of which I play obsessively myself — and Reiner Knizia’s High Society — which I think has as good of Artificial Intelligence and User Interface as any of our games and which I think plays well, but which doesn’t quite generate the same spark for continuous play for myself.

Five Points for Great Mobile Games

Why? Here are my best guesses at five elements that make for great mobile gaming:
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Making Computers Think Like Auction Players

Last week, RPGnet released the second of my iPhone games, an adaptation of Reiner Knizia’s High Society. To celebrate its release, I’ve opted today to continue my series of articles talking about adapting tabletop games to computers with a look at artificial intelligence and how the computer players in High Society “think”.

The State of the Art

So, how do you make a computer think like a human player? Today, it’s still somewhat hard to tell a computer to emulate the intuitive, off-the-cuff things that a player might do when playing a game. Surprisingly it’s even hard to write a good algorithm that thoroughly examines gameplay and makes a best choice; what a human does without even thinking has to be painfully programmed decision-by-decision into an Artificial Intelligence (AI).

Even with all of that, you’re not necessarily going to have a good AI. Becauase there are some things that humans will do better than computers, the only way to really make computers reliable is to make sure they take advantage of the things they do better than humans.
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