The REMA Model part 7: Application games

We’ve explored Rollercoaster learning, Experiment learning, and Mastery learning.  Finally, the last phase of the REMA learning sequence:  Application.

If REMA is a learning sequence, the first 3 phases are like the trunk of a tree, and Application is the branching out of that experience into player’s lives.  Application is the stage where players take what they’ve gotten from a game and apply it to outside contexts.  Where they use what they’ve learned, and share what they’ve gained. Where the output of the play becomes something to reflect and admire.  In a sense, once mastered, the play becomes performance to be shared.

Sometimes it’s literal performance, such as in social performance (Club Penguin) or comedy improv (Fiasco) or dance (DDR).  Other times it’s performance towards an end result, such as in art (Spore’s creature creator), education games in schools (SimCity, Oregon Trail), health (Superbetter), or stories (Alice and Kev in the Sims 3).  Application plau is play that deliberately use the play process to change people’s lives afterwards.

The design of this play is interesting, because this play is generative.  Designers are manipulating familiar kinds of plays to create surprising outputs.  It can be a masterwork of subtle manipulation of the other phases (Braid, Bioshock).  These games seem to me to be artistic goals of Rollercoaster, Experiment, or Mastery games, and better analyzed in that context.  (Often the Application play in these games was not intended!)  However, Application play designers are also exploring a new form of games altogether (World Without Oil).  These seem to be Application games.

Application games are still rare, and instances of Application play are far more common then games built for that purpose.  I’m not an expert in this area, so there could be a good deal more going on then I’m unaware of.  That said, the relative youth of Application games combined with the breadth of experiences means Application games don’t seem to share  traits as tightly as the other modes.  Only a few seem to have evolved so far:

  1. Shared External Goal.  The player(s) and the designer commit up front to create something, and work together to achieve it.  No jerks allowed.  (See the Narrativist paper RPGs.)
  2. Recognizable Output. Players have to be able to claim what is being created.
  3. Useful Output. Players have to be able to do something with it.
  4. Participant-Created Output. The players have an active role in shaping the output (otherwise, you don’t need the game part).
  5. Vague, Internal Success. Players need to be invested in parsing and promoting the output and declaring it finished.
  6. Tight Communities:  Performance needs an audience, and that combined with a valuable output leads to communities…
  7. Publication:  And “museum-like” repositories for the game’s output, often online.

Application game design is still young, and there’s much to discover.  But focused Application game designers are starting to appear.  The Serious Games and Narrativist Game movements are home to many of them, but others are light-hearted.  The advertising world is starting to take note, particularly in the non-profit sector.  The military is investing.  “Gameification” is a way of creating Application play in non-game contexts.  It remains to be seen whether Application games will evolve new game traits that evoke a new style of game, or whether they will focus on refining Rollercoaster, Experiment, and Mastery techniques for Application purposes.  But the unique pressures of performance create new possibilities.  I’d be curious if you’ve seen or heard of good examples that break the Rollercoaster/Experiment/Mastery game model.

So!  We’re through the REMA stages in detail.  Thanks for reading!  I hope its been enlightening.  We’ve seen how you can identify each play stage, some design traits that you can explore in each stage, and we’ve explored some of REMA’s shortcomings.  I have one more post planned on the relationships between the different traits.  But I’d also like to hear your take. Everyone seems to have a different perspective on it.  Please share!

The REMA Model part 6: The Mario Conundrum

Where does Super Mario Bros. go?

Let me tell you, in the REMA work Mario and similar games have been the biggest challenge so far for me.  Because REMA is based on a learning model and not a game design model, the categories aren’t defined by the games themselves.  It’s an interesting outcome that games seemed to have evolved to match these categories (likely a side effect of players being focused on only one mode at a time).  And it’s useful that these games have evolved unique traits that can help focus the design.

But Mario doesn’t fit.  Mario might be dismissable, because it was released well before most of the REMA traits had evolved.  But it’s an all-time favorite.  And there are plenty of other recent games that don’t fit well either.  Like Super Meat Boy.  And what about the Ninja Gaidens?  or Demon Souls?  The main design difference here from Rollercoaster games is just the difficulty.  But that difficulty forces the player to use Mastery-type play to proceed.  And player’s love it.

For any game, REMA classification is based on what is the primary focus of the player.  And the focus of the player’s play in these games 90% of the time is on perfecting a skill – Mastery play.  For the REMA model to be coherent, these are Mastery games.

But these games don’t share the traits I described for Mastery games.  They don’t have one room, they are a journey.  The structure is content driven and external.  They’ll often introduce new tools along the way that force you to restart the REMA learning process.  What gives?

I think there must be 2 kinds of Mastery games, each with a different lineage.  Mario is the kind of single-player Mastery game where designers create a series of difficult tests for players to beat.  By amping the difficulty, video game designers discovered they could create a different kind of Mastery experience from the historical, competitive Mastery game.  These games have very different traits from the historical games, from different evolutionary pressures:

  1. One Time Through Yes, you might play the levels over and over, and you might come back to 100% something, but these are linear games.
  2. Long:  And, like Rollercoaster games, to justify their value, they have lots of puzzles/levels.
  3. High Challenge:  Challenge promotes quick mastery.  These are often difficult cognitive (puzzles) or physical challenges.
  4. Punishment:  As does punishment.  These 2 are the key traits that separate these games from Rollercoaster games.
  5. Little Randomness:  A trait Mastery and Rollercoaster games share.
  6. Scripted:  The “beat it once” mentality encourages one-time construction techniques.
  7. Skill Driven: Progress is defined by tests of whether a player has mastered a particular skill or concept.  Unlike other Mastery games, the same test isn’t repeated twice.
  8. Direction:  These games are not one room games.  They are a journey, the player beating one test at a time.
  9. Content Driven:  The tests are a form of content.  Development is usually centered on content creation.
  10. Content Defined Stopping Point:  And when you run out of tests, you’re usually done.
  11. Varied, External Success:  The designer crafts the tests and the player overcomes them.
  12. Narrative:  Story serves as an excellent reward and frame outside the tests.
  13. Contextual:  The scenes and narrative often assist in the tests and slightly modify the systems, in order to vary and explore the scripted system space.

You’ll notice that nearly all of these traits are Rollercoaster traits too, except for the ones about difficulty.  And Rollercoaster designers have realized this too – most Rollercoaster games have an “Insane” difficulty mode that creates Mastery play.  Halo on Legendary is a completely different game then Halo on Normal.  The player’s goals and play are different.

This complicates things.  This makes 2 distinct groups of Mastery games, one of which is fairly close to Rollercoaster games.  And it opens up the possibility that there could be similar evolutionary splits in the other play modes.  We’ll see how it develops.  Do you think this is the right way to take the model?  Are there other groups I’m also missing?

In the meantime, I could use names for these 2 groups of games.  Ideas?

The REMA Model part 5 con: Mastered

One interesting type of play within Mastery play and Mastery games is that players aren’t always trying to improve themselves.  Sometimes players like to enjoy the mastery they already have, or enjoy the game’s explicit reward structure.  Doing their gathering rounds in WoW.  Beating new players in Dota.  Doing another round of Solitaire just for the enjoyment of it.  Players often just enjoy displaying expertise in Mastery games, only discovering something new and getting slightly better in a way that feels coincidental.

I think of this “Mastered” play as part of the core of Mastery play.  Often, our intrinsic enjoyment of something we’ve mastered is a big part of why we keep doing it.  Mastered play shares the design traits that Mastery play has, but it’s definitely a subgenre of Mastery play that has value (enjoyment) and pitfalls (grinding) of its own.

The core thing that separates broad Mastery and Mastered play is a player’s indulgence in rewards in Mastered play.  The REMA Model is learning focused, and doesn’t closely consider rewards and motivations from rewards.  REMA is just one perspective, and rewards design is another.  Rewards drive engagement and provide feedback in a way that is very useful for games.  REMA, for example, definitely exists on the different reward time slices we typically use (1 second, 5 seconds, 1 minute, …1 hour, 1 day, etc).  But REMA on the 1 second scale is not very enlightening: nearly all 1 second play is Mastery.  Reward design, however, is crucial on the 1 second level.

Game Thoughts: Hero Academy

I’ve been enjoying Hero Academy for iPhone, and rather then do a traditional Game Thoughts, I was inspired to do some traditional game design instead.

First, my best units in the game:

  1. Necromancer
  2. Ninja
  3. Archer
  4. Wraith

Why the Necromancer?  Because he’s

  • Range 3 with 200 damage and
  • can fully kill units at range 3 (instead of the standard kill range of 1).

Hero Academy is a game about using fewer actions then your opponent.  The Necromancer can guaranteed kill any unit in 5 actions at range 3 with 800 hp or less, without risking himself or his position.  No other unit can do that.  And 800 hp is the standard amount.  If the Necromancer has a sword, you even get a bonus action afterwards.

But the Necromancer is even better then that.  Being range 3 means you can hit them when they have to spend a turn to hit you.  Range 3 is safe.  And the range 3 full kill is even more important, since that saves you 2 turns (all other full kills are range 1 – so one moving in and stomping, and one getting away so you don’t immediately die).  I haven’t done it, but there’s a game designer with a matrix somewhere that shows # of turns it takes each unit to kill each other unit from “safe range” (which is normally range 3), and the Necromancer just wrecks that chart.  And the Archer is second, and the Ninja and Wraith are third (because they have move 3, range 1).  So the Necromancer is the best assassin in the game, in a game where assassination is nearly always the best play.  Plus, you get more Necromancers then you do Ninjas and Wraiths.  So, Hero Academy players, protect those range 3 units!

But, that’s all system balance-y stuff.  More interesting is coming up with your own team for Robot Entertainment to ship next:

The Dwarves.  Deploying unit heals all allies 10% of their health.

  • Cleric – 800 HP. 2 Move, 2 Attack range.  Heals friendlies 200 or revives them.  On attack, if in straight line also pushes back target and leaves square consecrated (enemy can’t step on next turn).
  • Bombadier – 800 HP.  2 Move, 2 Attack range.  Throws bombs for 200 Magic damage, can reach over blockers.  Also leaves bombs behind when moving, which if next stomped by enemy explode for attack magic damage.
  • Rifleman – 800 HP.  2 Move, 4 Attack range.  Shoots cannon for 400 physical damage.  Can only shot in straight line, and only 1x a turn.
  • Miner – 900 HP.  2 Move, 1 Attack range.  Swings pickaxe for 200 physical damage, does 2x damage to crystals.
  • Goliath (Super) – 2000 HP.  1 Move, 1 Attack range, 200 damage.  Shakes the ground with each step.  Think mechanical golem.  Enemies around destination take attack physical damage, and can get stomped.
  • Potion – Heals or revives and grants extra movement square on next move.
  • AoE – 3×3 200 magic damage AoE, enemies gets debuff that reduces next movement 1 square.
  • Scroll – 3x damage
  • Sword – 50% bonus damage.
  • Helmet – 20% MR, 10% Health.
  • Grog – 20% bonus health, heals for an extra 300.

Fun stuff!  So yes, I had to push the range power some more.  The core idea behind the Dwarves is unit coordination and board control, which is an orthogonal axis from the Council and the Dark Elves that hopefully would excite players.

Of course, without testing, these are probably mostly wrong.  Playtest, playtest, playtest.  My first area of testing would be if the Cleric Barrier, Goliath Stomp, and Bombadier’s Movement are too complicated, not the balance.  Hero Academy started with an admirable 2-line character description, and I might be pushing it too far here.  The Cleric Barrier also doesn’t manage range 2 diagonal attacks cleanly, which might be its doom.  But playtesting will probably find superior powers anyways, so I normally wouldn’t sweat it too much at this stage.  Making these games, you tend to end of with pages of power ideas lying around you can use.

Edit:  Also, this is like the most important Hero Academy post ever, and should absolutely be built into the “player info” screen.  It doesn’t count as hidden information (because all players have equal access) and is critical.

The REMA Model: Jean Piaget

A psychologist suggested to me that the REMA model is similar to Jean Piaget’s Sensorimotor/Adaptive model of Intellectual Development, specifically the Assimilation (Experiment) and Accomodation (Mastery) stages.  He said a first step, Observation (or Rollercoaster behavior) would fit the model as well.

REMA is built from playtest observation and discussion, similar to Piaget’s work, with a goal of starting from the player’s psychological point of view rather then a game design view, so this comparison is interesting.  Any other psychologists who could add to the discussion?

The REMA Model part 5: Mastery games

The REMA series continues. Recall, the hope is that by understanding the different modes and how they relate, we can improve the fractured conversation around games, and thus better understand and improve our games. Today, Mastery games. The oldest, most challenging, and most competitive games. And the games that have built the most dedicated fan bases ever seen.

Mastery mode is the third and often final stage of the gamer’s learning process. In Mastery mode players ask themselves “How can I do better?” Mastery players are trying to play the best, and they will play over and over again to do so. They are the optimizers, the min-maxers, the competitors, the soon-to-be-experts at their game. Mastery mode is what we historically played games for, and it is the REMA phase most unique to games from other mediums.

Mastery games maximize the Mastery mode of play. They try and get players quickly to the third stage and keep them there with deep, unsolvable systems. They are about expressing skill. These are games about competition, player vs. player, and playing to win. They are the “Try again” games. These games are more then just interesting choices. They are about interesting predictions as well, about beating the average. While difficult to make and sustain, they have the most dedicated players. The Mastery designer’s primary role is to provide systems that can’t easily be solved, and where success and failure can be measured relative to some external standard.

Chess. Poker. Soccer. Mine-sweeper. Street Fighter 2. Magic: The Gathering. Counter-Strike. Starcraft. Games that have carved swathes across human culture for generations. Nearly all board and card games are Mastery games. While competitive play is common, Mastery games can be single player too, such as Solitaire. The key is Mastery games present success as a repeated quest for victory. Mastery player’s repeated attempts at perfect play fits the world of sports and races. In fact, they are so similar that I often just think of sports as Mastery games. It is no accident that eSports have arisen out of Mastery games, and only Mastery games.

A reminder here. The players choose how they are going to play your game. While X-Com might be an Experiment game, the 10th time through a player is very likely to be a Mastery player. The designer only has the power to guide players through the modes. And, because of the traits of each mode, designs can usually target only 1 mode at any given point of play time*. So when we talk about Mastery games, we are talking about games that were designed to be mastered by the majority of its players.

Mastery games are hard-core, by definition. You aren’t just playing any more, you’re striving. You’re practicing. You’re competing. You’re earning victory. Our verbs change from Experiment verbs (like “play” and “imagine”) to sports verbs. We all engage in Mastery play at some point in our lives, but it’s not often we commit to it seriously. But when we do, that game becomes special. And when other people start to push the boundaries of perfection, we love to stop and watch.

Mastery play has evolved Mastery games over centuries to share common traits:

  1. Deep. Can’t be easy to master. The best mastery games are not just deep, but unsolvable.
  2. Highly Replayable. The best path to mastery is to practice over and over and over.
  3. Very Short. Short games make it easier to learn from your mistakes, analyze, and try again.
  4. Balanced. The game can’t have optimum choices that preclude all other choices, or it won’t be worth mastering.
  5. Low Number of Choices. Plus, lots of choices can make the game harder to learn and perfect. Thus, “elegance” is highly prized, designing the minimum number of choices necessary to make the game meaningful.
  6. Punishing Consequences. The results of player’s choices must be significant to distinguish experts from non-experts. Mistakes are often punished.
  7. Little Randomness. Randomness used carelessly can hide skill, so it is only used in strict, analyzable chunks.
  8. Skill Driven. Expertise is about demonstrating skill, so Mastery games are full of difficult skill choices.
  9. Difficult to Execute Skills. Additionally, skill can be demonstrated in execution, so choices often require difficult to execute skills (such as physical dexterity).
  10. Analog Choices. Another way to make choices difficult-to-master is to make them analog (as in choices with infinite possible responses, like timing, moving, or aiming through space).
  11. Clear Game State. To optimize your play, it helps to understand all the details of play. Lots of exposed numbers, and clear “Do X and Win” are the designer’s marching orders. No mystery or surprises.
  12. System Driven. Choices means systems first, not content first. That makes Mastery development teams similar to Experiment teams, except they are focused on very tight, sharp systems.
  13. Specific, External Success. What it takes to win a Mastery game is often very clearly defined, either by the designer or (interestingly) the community. For example specific end states (like Capture The Flag), leaderboards, or other players failing a task.
  14. No Cheating. Unlike Experiment games, breaking the rules is strictly forbidden. Winners need to be unambiguous. Referees are common, and cheaters are banned. (One of the big knocks against figure skating as a sport is that the scoring is perceived to be corruptible.)
  15. One Small Place. Mastery games take place in small arenas, if they have a space at all. Tighter spaces limit choices, force difficulty decisions, and push players towards thinking about mastery.
  16. What Narrative? Narrative is seen as distracting, for someone else. Any themes of the game are either an oft-ignored content veneer or deeply buried in the game’s systems.
  17. Regular Design Updates. One common way to make a game both unsolvable and balanced is to constantly change small pieces of the rules.
  18. Tight Communities. The deep analysis, the commitment to master, and the (common) multi-player requirement tends to create very tight, dedicated communities.
  19. Meta-game. The discussion and analyze of the group creates a meta-game around the game itself. Updating tends to feed this meta-game as well.
  20. Audience. Tight communities and meta-gaming often leads to groups more interested in watching experts then playing themselves.

Of these traits, Highly Replayable, Very Short, Balanced, High Consequences, Analog Choices, Difficult to Master Skills, Clear Game State, No Cheating, One Small Place, What Narrative?, Regular Design Updates, Tight Communities, Meta-game, and Audience are unique to Mastery games. Mastery games are rather unique! Most of the other traits are shared with Rollercoaster games, which has helped the long-running blockbuster trend of combining a single-player Rollercoaster game with a multiplayer Mastery game.

Like Experiment designers, Mastery designers are often systems designers. But they are in search of elegance rather then emergence. They know how to create deep, unsolvable systems. To get players to “Try Again” over and over. Many are PvP game designers or interested in the behavior of communities. Mastery designers often seek to affect primitive emotions – aggression, dominance, fear, adrenaline, victory, flow. The best can carve those impulses into meaning, teaching deep truths about how humans tick and skills that improve player’s lives.

Historically, Mastery games pre-date computers, and made the transition rather roughly. Traditional video game critics often don’t even have the time or a competitive environment to effectively review a Mastery game in, and their scores have correspondingly suffered. And while intensely popular with their committed fans, Mastery games tend to have the smallest initial audience, and thus made the least amount of money in the storefront business model. These have been changing, however, and mastery games are making a big (and largely unnoticed) comeback.

Their sub-genres need further study. Obvious starting points are PvP games, solo-games, and cooperative games, but the mechanical distinctions seem deeper then that. If you have any thoughts, post them in the comments!

Next time, our final and strangest mode – Application!

* It’s not a hard rule that games can only have one REMA mode. It’s not like designers should stop making games that don’t easily fit into these categories. The evidence is that it’s just particularly hard.

Edit: added skill-driven trait.

My Most Interesting Games of 2011

What were your top games in 2011? Consider all games eligible, board, video, card, etc, even if they didn’t come out this year. What was the most interesting game you didn’t get to play? What was the biggest non-personal innovation to your gaming this year?

Mine are here:

Most Interesting:
Minecraft.  First year I’ve really got to experience the social side of the game, and experienced the community mechanics and roles. A real revelation about social game design.

League of Legends. Serious ultra-competition. I’ve played more of it then any other game, and it’s now the largest western online game.

7 Wonders. Drafting made made accessible, while still deep.

Echo Bazaar. Game I just kept coming back to. The qualities system I find very inspiring.

Jejune Institute. I had a blast with this. The combination of city history, puzzle hunting, character drama, and good exercise was a great revelation for me, too.

Tiny Wings. A simple game I played nearly every day for months. One button done amazing well.

Most Interesting Unplayed:
Capes. I’ve read a lot of RPGs this year, and this one stood out. GM-less, simple, unlimited power level, all with an interesting system and narrative combo. Seems like a great gateway game.

Johann Sebastian Joust. Everything I’ve heard about this game sound amazing. But playing it feels like I first have to win the 6 degrees of separation game.

Biggest Innovation:
My iPad. It got me to junk my laptop, which I didn’t think would ever happen. The world is a different place now – instant on portable, light, touch sensitive, and full of new games.

The REMA Model part 4: Experiment games

Our series on REMA continues.  We’ve looked at the Rollercoaster games, next up: Experiment games!  The most complex and messiest of games.  The most random and yet most interactive of games.  Onward!

Recall Experiment mode is the second phase of any learning process.  When in Experiment mode, we ask ourselves: “Now that I know what tools I have, what can I do?” “What can I achieve?”  It is the mode of over-enthusiastic scientists, the mode of explorers, the mode of game dynamics.  The mode for players who want to discover the systems that craft themselves from the game mechanics they’ve learned.

Experiment games are games that emphasize Experiment mode.  Experiment games are about exploring systems through choice.  They are the “Or” games.  I can do this or that.  Where there’s no one best option, but there are lots of interesting options.  They are the games in Sid Meier’s “A series of interesting choices” game definition.  The games for Johnny (of Mark Rosewater’s Magic: The Gathering psychographic profiles*).  This is not your polished, trimmed mega-hit.  This is the home of the mechanically behemoths, giant inventories, and open worlds of gaming.  The Experiment designer’s primary role is to provide interesting tools and systems that create predictable results.

Civilization, The Sims, SimCity are the granddaddys of this genre.  But the first was possibly Dungeons & Dragons (1st & 2nd editions), which had simulation at its core (see their rules breadth and what they publish as supplements).  For other examples, consider X-Com, which asks  “Anything could be out there, how are you going to deal with it?”  Or Minecraft – where the core Experiment play is not the simulation per say but what you can do with it.  Or Dwarf Fortress and Animal Crossing – Experiment games that present worlds of gameplay options instead of simulation.  Experiment games are also the true home of emergent and open world games like Skyrim, Deus Ex, Bioshock, and Grand Theft Auto 3, which have long struggled with their Rollercoaster roots.  All Experiment games share a common heritage of play.  Experiment games are the home of choices, and encompass system investigation and the surprise of discovery.  Thus, it is the genre of games closest to toys, and much of its design springs from the same place, if for an older audience.

Man, I love me some Experiment games.  Ahem.  Experiment games are driven by their rules.  They are the gamiest of games and the most computational of games.  They craft elegant simulacrum out of rules.  They think about the real world.  They ask “What if?” with interaction.  And man, compared to other games, are they strange.

Experiment play has evolved Experiment games to share certain traits:

  1. High Number of Choices.  Experiment games are all about seeing what things do when they interact.  So you need a lot of things.
  2. Emergent Choices.  And you get even exponentially more choices if you have the choices affect each other.
  3. Interdependent Choices.  Even better, interconnecting choices together can create new choices and complex decisions.
  4. Procedural.  And procedurally generating choices can create choices forever.  Mwhahahahahaha!
  5. Long.  Seeing what happens with all these choices takes time.  Particularly when choices are dependent on earlier choices.
  6. Yet Still Replayable Despite being Long, the large number of choices encourages players to start fresh several times.
  7. Predictable Impacts.  Making frequent choices means rapidly understanding what they will do.  This becomes even more important when there are lots of choices interacting at the same time.
  8. Digital Choices.  Choices with discrete states like [on/off] or [0…10] (as opposed to analog choices like aiming or free moving) have outcomes that are much easier to predict, follow, and replicate.
  9. Low Consequences.  Likewise, low consequence (and thus low challenge) let players explore their options freely and repeatedly.  Not to mention, if there are only a few relevant choices, well, it wouldn’t take long to figure out the best ones, would it?
  10. Time to Think.  Low challenge digital choices mans few physical challenges (things like click speed or reaction speed).  Plus, giving you time to consider all the magnificent ramifications of your options before you select one creates the illusion of even more choices.
  11. Mystery.  Even though clear immediate choices with low consequence are desirable, Experiment games want to preserve a sense of long-term mystery.  Otherwise, the right choices would be obvious, so why would you even bother experimenting?
  12. Randomness.  Experiment games also use the most randomness, because randomness makes picking the same choice twice more interesting.  Randomness is also very useful in building interconnected choices, maintaining mystery, and making choices and simulations seem more varied.
  13. System Driven.  Experiment games, being choice-driven, are about systems first, not content.  This means they are built in a completely different way, relying primarily on top notch design rather then polished art, sound, and other data.  Experiment development teams are much smaller then the modern Rollercoaster teams and use different production techniques.
  14. System State Ending.  Being system driven, the end of an Experiment game is defined by reaching a specific rules state, not reaching the end of a content flow.
  15. Varied, Internal Success.  Accomplishments in Experiment games are defined by reaching rules goals.  Most of the time players are involved in choosing their own end state, rather then the designer.  Sometimes the systems suggest an obvious end (such as “other players are eliminated”).  Other times, winning is not defined or is defined outside the main game and often ignored.  Have you “won” Minecraft?
  16. One Large Place:  Because of the large number of interconnected choices, Experiment games fold in on themselves, repeating interactions in same space.  Thus, instead of a journey, Experiment games are like sandboxes – self-contained worlds that you traverse many times.
  17. Mixed Narrative:  Experiment games are so simulation-oriented and player-driven they are not usually a good fit for narrative messaging.  Plus, it is difficult for designers to craft a narrative that occurs during play.  Some messages can be embedded in the content (usually in the form of radios or overheard dialog), but these are often undermined by the stronger messages embedded in the systems themselves, which take time and expertise to decipher.  Experiment games also often form the seeds of Player-defined Narrative, which ties them closely to the Application mode of play.

Of these, High Number of Choices, Emergent Choices, Procedural, Time to Think, Randomness, Varied, Internal Success, and One Large Place are all unique to Experiment games, and the others differ from either Rollercoaster or Mastery games (Experiment’s REMA neighbors).  These game traits create inflection points in a game’s design – forcing the modes apart.  As a designer, adding one mode’s traits will naturally push you to add more and more of that mode’s traits.  If you have large amounts of randomness in your design, you’ll find your players pushing other Experiment traits on you, because your players are playing your game in Experiment mode, and they want to stay there.

Experiment designers are often systems designers.  While setting and world building are important to some Experiment games, most thrive off their choices.  The expert Experiment designer can create systems that emulate a fantasy, abstracting away the perfect amount of detail while immersing the player in that world.  The expert Experiment designer creates systems that inspire the imagination, and can get players to exploring every nuance.  And the expert Experiment designer creates deep meaning out of these nuances, as they players come to truly understand what these systems say about the world.

Commercially, Experiment games have been middle-of-the-road between Rollercoaster and Mastery games.  Experiment games require more comprehension from the player then Rollercoaster games, which might explain their lower quantity and lower popularity.  However, the breakout hits of the Experiment genre have also been huge hits.  Players love playing with reality.  “What can I do?” can seizes the imagination in ways no other genre can.  Plus, a good Experiment game offers better value, often getting several plays and better avoiding the used bin.  Experiment games are notoriously hard to review, because they are so player experience defined.  The whole point of an Experiment game is your choices are your own.  In fact, it’s often easiest to review what they aren’t, rather then what they are.

I’ve found a few of the sub-genre offshoots within the Experiment genre, some of which dramatically push one tenet in its opposite direction as far as it can go:

  • Simulations, highly interconnected choice spaces that emulate something specific,
  • Real-time games that embrace rather then avoid the physical challenges like click speed,
  • Permadeath games which have permanent death or limited total turns to encourage experimentation through fatal consequences (often with limited success), and
  • Immersive games which strive to embed you in the game world itself, that create the illusion that you are actually there and that you have every choice a character of that world would have.

Immersive games have been in the news.  This subgenre inspires radical jealousy in Rollercoaster designers because it deeply engages players in avatars and settings, but the tension between Rollercoaster and Experiment games makes it very hard to achieve immersion outside of an Experiment context.

Halfway there.  Next:  the newly revived Mastery games!

* Mark Rosewater’s Timmy is, of course, the psychographic similar to the experience-driven Rollercoaster players, and Spike, as we’ll see, is a Mastery player.  Vorthos and Melvin are forms of Application players.

Game Thoughts: Batman: Arkham City

Batman: Arkham City on X360 by Rocksteady. Time Played: 14 hours.  Status: Finished.

  1. An open world game doesn’t feel open world when loading screens happen every 5 seconds and the game crashes.  I don’t think it was worth it.
  2. I am lost.  “Landmarks are needed!”  A good introductory tour of the City could have done wonders.
  3. The open world phases make the game muddle.  I much preferred the more linear rollercoaster stylings of the prequel.
  4. Excellent neon signage.  Batman Forever eat your heart out.
  5. The best swinging I can recall.  Spiderman has really established this gameplay style well.  The gliding took a lot of time to get used to, however.
  6. The combat is still textbook awesome.  And the critical hit system (which rewards you for not button mashing) combines with the old combo system brilliantly.  Give that man a raise.
  7. Mixed boss fights.  The Mr. Freeze fight (when you have a good stealth system, flaunt it!) and the Ra’s Al Ghul fight are both big standouts.  Most of the others fall short due to story placement rather then the fight itself.  Lesson: build your fights to fit the feelings, if you’re going to write your story ahead of time.
  8. So many buttons and gadgets though, I struggle to know what I can use when.  Good thing Strike and Counter are so reliable.  A slower gadget intro rate would be my main request.
  9. For their complicated controls, they still are masters at tutorialization.  Nicely layered test rooms and optional missions that train you in a specific move one at a time, spread over the first 10 hours.  Dedication.
  10. And hint text every time you use a rare or contextual action, or they even guess that you might want to.  Fantastic.  The kind of AI no one notices, and yet is absolutely required.
  11. So Many Villians!  No game other then Batman could even attempt it.  3 would have been plenty.  Villian introduction rate: 2 per hour.
  12. Grungy.  Everything is so grungy.  The palette seems remarkably narrow.
  13. Side quests and rapid pacing still don’t mix.
  14. The Riddler’s secrets feel more like pedestrian hidden objects and achievements this go round.  My guess: the open world-ness makes it feel less like you’re “finishing” a room.
  15. The Catwoman “Buy-or-Pay” model can’t shake the DLC feeling, no matter how many times they ask you to pay before you start the game.
  16. What’s up with the ending?  A story collapse moment for me.

Batman: Arkham Asylum still stands out to me, but this game made me nicely nostalgic for it. (Disclaimer: I used to work for SquareEnix, the publisher, but have no connection with the work itself)

REMA wrap-up:

  • Primarily a Rollercoaster game, with the player being driven forward by story and mission goals.  Plenty of classic Rollercoaster touches.
  • Nice isolation of the various systems (stealth, combat) with clear delineations allows some manageable mode switching.
  • However brief encounters, short-lived successes, inability to repeat encounters, and longer load times limits the opportunities for Experiment and Mastery in the main game.
  • Some Experiment possible in the Combat system (lots of gadgets, XP for variation) and in the Stealth system (lots of options for takedowns, XP for variation).
  • Primarily Mastery in the Challenge modes, outside the main game (start with same set up every time, global leaderboards, easily replayable).