Recent Ubisoft games have been observed to share a lot of game mechanics. The formula gradually evolved through the years but took its roots in the first open-world title of the company, Assassin’s Creed.

The core system of this formula is the Reach high point mechanic, that lets players make Altair climb a tall building, synchronize to unlock all quests in the area, and jump down through a signature Leap of faith.

As I had the chance to participate in its design, I would like to share with you how we got there, and what made the system so successful that it’s still used in games, 8 years after its debut. As you’ll see its strength can be analyzed through the lens of biology and psychology.

I believe the strength of this mechanic lies on how strongly it motivates players. This is achieved through proposing a clear objective, and a significant reward that immediately follows challenge completion in a very tight loop. This echoes the conditions for flow stated by Csikszentmihalyi that create maximum engagement when performing tasks. Let’s deconstruct the different components that make this system so rewarding and efficient.

The first characteristic is that the reward of unlocking nearby quests comes immediately after synchronizing. This creates a strong and apparent link between cause and effect that brings clarity to the system. The direct reaction to the players actions also represents a dopamine-based reward. It is Nature’s way to motivate us to impact the world around us.

Secondly, the fact that multiple quests are unlocked at once increases the pleasure response as it reinforces the player’s feeling of agency. The bigger the difference between a small action and a big response, the stronger the dopamine release, motivating us to create strong consequences.

The initial design for this system involved talking to characters hidden outside of cities in order to unlock individual quests players had to travel to. These two factors explain why having multiple quests unlocked immediately available creates stronger reward.

The pleasure created by a tight loop with immediate and important reward mimics kids reactions when they press elevator buttons, get the immediate visual and sound feedback and put the whole cab in motion.

Another aspect is the fact that this system grants intrinsic rewards. Instead of extrinsic abstract prize like gold that the player would have to trade in, the player now gets access to more challenge/reward loops. Not only intrinsic rewards are more satisfying, but they also increase a player motivation and engagement with the activity, compared to extrinsic rewards that rather encourage players to exit the current loop, and literally break the flow.

References:

1. Wikipedia- Flow – link
2. Gamasutra – Addiction and the Structural Characteristics of MMO Games – link
3. Youtube – Drive: The surprising truth about what motivates us – link

In the previous article, we’ve looked at gameplay from the perspective of a symbolic system that proposes abstract problems to players, and that requires structuring norms while allowing for variation and uncertainty.

I commend you if you survived through part one and its heavy-handed theories, now is the time to explore this approach and see how it can inform the technique of game design.

Gameplay principles

Mel Brook’s 15 commandments

Symbolic systems work within the constraints of high level rules. Like music function with harmonics and rhythmic scales, gameplay should also have its own set of governing principles. Now, it is quite a responsibility to state such laws and this proposition is in no way definitive. It is rather a contribution to a collective effort of defining our craft that I invite all to participate in. Here are the principles that I believe need to be observed when creating gameplay. They shouldn’t come as much surprise, but they are nonetheless important to keep in mind.

Fairness: Each player (or starting position) should have equivalent chances to win, or roughly equal. This applies to symmetrical games like Capture the Flag, slightly asymmetrical ones like Chess and Starcraft or games that propose widely different roles like Left 4 Dead.

Consistency: Game systems should demonstrate causality and consistency. Games should propose systems with reproducible behaviour. Even if their logic might not be initially obvious, players should be able to establish a mental model to make informed decisions. Games should still allow for uncertainty though as they might lose any entertainment value if they become too predictable.

System clarity: A game should contain all information necessary to evaluate a position and determine the correct play. Granted a valid mental model has been established, no element required to make the right decision should be missing from the game. They can be hidden or cryptic, but like a puzzle or an exercise of mathematics, the rearrangement of the elements provided should be sufficient to find a solution.

Strategy balance: All available strategies should have relevance and value, while none should be dominant and without counter. Useless strategies are counter-productive, while unstoppable ones just outright destroy any game.

Payoff balance: Reward should be proportional to the risk incurred. A powerful item should be difficult or risky to obtain, a safe path should bring limited rewards. Typical examples are games like Roulette, where the payoffs are aligned with the odds or multiplayer games where the most powerful items are in exposed locations.

Skill relevance: Skill should represent an advantage, and the most skilled player should have more chances to win. Games are activities or learning and personal betterment, they should promote the research of optimal play and thus increase the chance of winning of skilled players.

Respecting all these principles is sometimes difficult, and it is interesting to note that competitive games often balance an unfair situation by adding meta-rules that encapsulate the game itself. This is the case with Chess competitions that have matches based on multiple rounds. For each match, multiple games take place and players alternate between the two sides to account for the advantage white has of playing first. Alternatively, games can deliberately decide to stray from these principles for artistic, entertainment or accessibility purpose. It is the case with catch-up mechanics, common in games with a mass-market target like the Mario Kart series. It also is a strong way to make an artistic statement. For example, the game Cart life provides a confusing gameplay to convey the difficult experience of adapting on the fly to life-changing situations like immigrating to a foreign country. Tampering with these principles is rather risky though, as they might break the game dynamic, the challenge, or make the player experience difficult. This should be reserved for experienced designers and those new to the discipline should exert caution and stick to those principles as much as possible.

Taming emergence by defining winning play

Games are made of a multitude of elements in interaction. Adding, removing or modifying any of them can have very important impact on the way games operate and on what they offer players. The emergent nature of gameplay makes creating a game by juxtaposing features quite risky, because even if they seem interesting on their own, their interaction may create broken dynamics. It would be similar to throwing words together hoping that a sentence would actually mean anything. In order to shape the emergence of a clear enough gameplay for players to understand, I recommend first establishing a target before choosing what element to include in your game. I call this defining the “winning play” that players will have to learn, as well as its different variations that they will explore along the game.

A winning play is a unitary way to be successful against a specific challenge, one technique the player has to learn to solve a type of problem. In Super Mario Bros, the key principle to kill monsters is to jump on their head. It will suffice to dispose of the simplest enemy, the Goomba. But soon, Mario faces Koopas that take two hits before being defeated, or Spinies, enemies with spikes that can’t be jumped on. After having assimilated the case or reference, the player faces more complex situations that add steps on top of the initial winning play scenario.

A winning play should be established in the early stages of a game and repeated enough times for the player to assimilate before increasing complexity. In Gears of War 2, Marcus Fenix states it during the first moments of the game as he teaches the ropes to a new recruit.

Golden rule of the Gears is: Take cover or die

This golden rule is not simply about learning the controls of the cover system, but instead about the tactics built around taking cover. The game is tuned so that fighting in the open is a losing strategy, and the first encounters are set to illustrate and teach the importance of cover. Then other systems are factored in and more complex concepts appear. Enemies also take cover and, because they can be revived by their teammates when downed, a static strategy behind protection becomes a stalemate. This introduces the concept of flanking in order to nullify their cover and kill them before they can be revived. Finding the vantage point and reaching it is one additional step to take before putting yourself a winning situation where you can gun down the opposition without risk. But what if reaching a flanking position will put you in the open and draw too much fire to you? Then maybe you can wait until the enemies reload, create an intermediate cover or incapacitate enough of them so you can dash to position while they get revived.

All game elements are designed to make this situation the recurrent theme of gameplay, and the player learns the basic rule: Fighting an enemy from cover is a winning situation. Then as situations get more complex, he learns all the tricks to put himself in the conditions of the winning play. Furthermore, multiple game features point back at that key challenge of taking cover, making the whole experience coherent and consistent: Shields that let you plant a cover where needed, enemy to be used as meat shield, invulnerable rock worms to hide behind as they move which let you access a vantage point… All contribute in and deepen the concept of cover, lending a symbolic nature to gameplay that make it a focused learning experience. As elements “magically” fall into place, the player is bound to experience his very own “Eureka!” moment as he figures out the pattern you designed for him.

If you consider a game as a learning tool, then designers should figure out what the lesson is before building the curriculum. Stating that winning play and defining all the variations to that rule will ensure that your game provides a clear and comprehensible concept to the player. It will also give you a target to aim for when implementing your game mechanics and will help to select ideas and features by evaluating how adequately they factor into a coherent gameplay.

The search for true form

Within a game’s construction of moving parts is one more notable than the others: the player, with his or her drive to evaluate the system and find solutions to implement. Designer and competitive player David Sirlin describes a game as a debate between players using the game as a language and plays as argument, trying to find which strategy is the best (Playing to Win, 2000). Through this research of optimal play it is possible that the discussion moves beyond the direct satisfaction of the winning conditions. A different point of contention appears: the true form of gameplay.

Even though the rules of Chess state that you win by checkmate, putting constant pressure on the enemy king will most probably not lead you to victory. Street Fighter is not about taking your opponent’s health to zero but rather, as Sirlin explains, about reading your opponent’s intentions, controlling space and pressing an advantage. Similarly, the true form of Tetris is not to arrange falling tetrominos to clear lines, but instead the higher level dilemma it proposes is to choose between two strategies: To hold off and wait for opportunities to clear multiple lines at once to score more points, or to clear them at any occasion possible to create more breathing room and avoid a game over. Although very limited, all the features of Tetris contribute to this choice between short- and long-term. Game speed gradually increases with music pace as feedback, making you reconsider your strategy as the board gets more cluttered and pieces fall faster. The display of the next piece also informs your choice, and some versions let you hold one piece deepening even further the core question. The way all game features converge toward a unified issue is what provides a symbolic nature to gameplay and make it interesting to engage with. Once again, a deliberate approach is recommended so as to give a clear target to our design efforts by determining the true form we want to see appear.

An interesting decision offers clear choices, the best one being difficult to determine

This top-down approach receives frequent resistance though and it is not uncommon to hear students and design veterans advocate for gut feeling and a more “old-school” attitude. While I wouldn’t dare argue with genius and pure inspiration, I believe that having a process that lets you plan ahead and discuss decisions before committing seems reasonable. Minecraft is often cited as an example of a successful game based on “emergent gameplay” (which I think is a pleonasm) and an argument against an organized top-down design approach. While its world generation is largely random, its game systems still display a large amount of structuring rules in the form of item recipes, creature AI and resource distribution, to name a few. This lets players make their own assumptions and verify them in an experimental manner through interaction. It is the alliance between structure and variation that is at the core of gameplay and we will explore how it applies to its design in the following part of this article.

Sources of structure

Hitboxes in Counter-Strike

The defining element of a game is its set of rules which provide structure to play, an explorative behaviour of the player. As a symbolic representation of a problem, gameplay must offer a clear and pure abstraction that eliminates distraction and let players establish a mental model and carry on his or her research of solutions. This is why game systems should be consistent, and behave in a predictable fashion to allow an experimental approach so the player can ultimately understand them. Clarity is also a typical source of structure and supports the symbolic nature of gameplay. Implementing winning plays with binary success conditions helps establish clarity and the development of a mental model. It is especially important for game mechanics that are central to gameplay. For example, jumping on an enemy in Mario is a binary event, and even in a first-person shooter with a wider freedom of movement hitting a target is treated in a binary fashion: you either hit or you don’t, the effects are all-or-nothing and there are no flesh wounds. It is notable that the notion of feedback clarity for your actions is one of the conditions that Mihaly Csikszentmihalyi establishes for an individual to enter a state of flow (Flow: The Psychology of Optimal Experience, 1990). This seems to indicate a link between the structured quality of gameplay and its properties regarding motivation and engagement.

In Starcrat 2, expansion choice is structured by resource repartition

Player choices themselves can be structured, and should appear as deliberate in order to reinforce the symbolic nature of gameplay. By designing the game systems to create cascading decision branches for the player, we can consolidate true form and let a coherent point of contention appear to the player. The true form of Starcraft’s gameplay is to distribute resource between the development of economy, army or technology. The way harvesting is structured both in systems and location create discreet jumps that force a deliberate choice from the player with sustained consequences over time. Mineral patches and gas geysers are always arranged together in a base-shaped setting called an expansion. Because mineral patches can only support a limited amount of harvesters, a player trying to increase his economy will have to develop to a new expansion by building a base and a set of harvesters. Because of the required investment in resources and time, the economy of an expanding player will effectively increase only after a few minutes, leaving him vulnerable to any opponent who selected to invest in an army to attack him. These discreet jumps in efficiency are the structure that creates clear interplay between player strategies. Starcraft 2 features the same type of deliberate choices in the technology development path. High tier units such as the Protoss’ Colossi require multiple buildings to be constructed, and only fully pay off after additional research is done and enough are built, leaving you open for a lower-tech attack in the meantime.

This is similar to the way advanced special moves require EX meters in Street Fighter 4, or even the fact that jump attacks that can’t be blocked with a low guard force you to go airborne, and thus be on a predictable trajectory. Gaining an advantage requires a commitment and strategy would be irrelevant if it was possible to change options without cost. These elements of restriction and structure are the grammar of the discussion between the players Sirlin describes as competitive play.

Variability requires structure for gameplay to remain symbolic

As mentioned in earlier articles, variation, uncertainty and freedom are essential to play and fun. Witnessing unpredictable events creates excitement and engagement as proven by studies on variable reward patterns, yet a fully random situation has limited interest as a game environment. Let’s look at how balance between variability and structure can provide interesting gameplay.

Randomness

Randomness is the most immediate source of variability, and it is notable that the unpredictability it introduces is generally frowned upon by dedicated players, especially in competitive circles. It is true that a game that would be decided by a dice roll would basically throw out of the window most of the principles we’ve enounced in the first part of this article, especially consistency, system clarity and skill relevance. Such a game would give an extremely limited value of player actions and although it could be entertaining, it would not have much potential in terms of competency development. Randomness is valuable as a way to introduce unexpected situations that let players adapt, and is best used if players can have some control over it, impose some structure on it.

At the opposite end of card game reference Magic: the Gathering, Hearthstone is a game that features a good amount of cards with random effects that can be deciding factors. The Mad Bomber inflicts three points of damage spread randomly on the board as he is played. This can seem damaging to the competitive value of the game, by removing control from the players and thus minimizing skill relevance, but it is to be put in perspective with the fact that the game lets participants shape the situation in which they use such a card and thus shape the odds; structured variability. Players can select the right moment to play such a card and thus pick a situation where the odds are favorable. They can also affect the board using other abilities to shape so the random behaviour of the Mad Bomber has higher chances to be beneficial. Because building your deck of cards is part of Hearthstone, players can also shape the odds of having the right combination of cards to maximize effects, even if they are random. In fact, building a deck is structuring variability by itself. This is similar to the different types of games of Poker where the choices players have can be used to structure variability by betting amounts of chips in relation to the odds of winning and potential pot payout. Structuring variability is the core of player actions in such games.

Execution

Execution is another type of challenge that brings uncertainty into a game. Having to master a system based on physics or on real-time constraints is a valid way to introduce variability into a game. It is important to note that the depth of the resulting challenge is linked to the complexity of the system itself and so will the skill cap of the game be. Depending on the targeted audience, the desired level of complexity might vary, and if building a complex enough simulation is out of reach, additional depth should be introduced by supporting features. Real life is a rather complex system to master, and this is what makes the sport of Archery deep enough that enthusiasts can dedicate their whole life developing their mastery of it. By contrast, even if the physics of a game like Quake are quite complex, players tend to achieve very similar degrees of shooting accuracy at the highest levels, and this mechanic loses relevance as a deciding factor. The presence of an additional level of challenge through map and item control increases skill differentiation for this game. This is probably what makes Quake deep enough so players can still be engaged in its mastery almost twenty years after its release.

System interaction

Simple systems used in conjunction can also be a valid way to create uncertainty. If multiples of them interact and feed back into one another, the ensemble can create initially unexpected behaviours. Figuring out how they function together then becomes a challenging and rewarding activity. The way interconnected systems work is typically depicted using the butterfly effect where one small localized cause can have drastic consequences across the planet. Very simple and easily predictable independent systems can sometimes synchronize and have results that go way beyond initial estimations. It is the case with the resonance phenomenon, when oscillating waves can see their energy amplified when they match in frequency and destroy structures of different sizes, from a drinking glass to a bridge or a building. To an extent, rocket jumping is an example of how different systems can interact and provide results out of the initial scope, sometimes even of the game developers themselves. This possibility wasn’t planned for when it appeared in Quake, but it gradually got adopted and incorporated in a deliberate fashion with the addition of the battle suit item that cuts on splash damage to encourage players to move around by shooting themselves through the air, or through level design actually designing space to make that option more relevant. The cancel mechanic that first appeared in Street Fighter II as a bug was capitalized on in later games of the series, becoming a hallmark of fighting games at large. As discussed earlier, it is best to plan for these emergent behaviours and introduce the different systems through the atomistic exposition of the winning plays that a player can gradually learn before understanding how they combine them.

Restricting information

Different types of information availability (Magic: The Gathering)

The notion of information availability is a defining characteristic of games as established by game theory. Games of perfect information like Chess let the whole game state be completely visible to all players at all times. Games of imperfect information limit the perception each player has of the situation, introducing a dose of uncertainty that forces participants to work with assumptions. These games should make sure enough information is communicated between the players in order to structure the possibilities and give tell-tale signs to allow attentive players to make the right choices or the employ deception. In Poker, bets are shared information so the involvement players make in the pot can be used to evaluate their hand strength and bluff becomes possible. Without this exchange of information, the game would become too uncertain and no winning strategy could be developed. Strategy games like Starcraft typically use fog of war to restrict information access. Obtaining information becomes a key part of the game as very strong strategies that can be developed and require specific reactions. This is why dedicated scouting tools are made available to players. The fact that strategies require a thorough investment in time and resources to be efficient is what makes scouting and bluffing relevant in such a game, as we described earlier when we explained the value of structuring deliberate player choices.

Amount of possibilities

A high amount of available options is also a source of uncertainty that is frequently used in games. Wide variety of choice can create a large space of possibilities that is worth exploring for dedicated players. For example, Chess offers many different moves each turn and the number of different games is said to be astronomical. If the options offered to a player lack strategic relevance, selecting the right move can be quite confusing as the process becomes purely computational, better handled by a machine than the human brain. If the choices follow different strategic themes, players can operate at that high level to first select an approach. This gives them a subset within the pool of options so they can then evaluate solutions at a tactical level. This distinction in level of abstraction allows a large amount of choices to be offered to players while organizing them within thematically meaningful groups that help the decision process. It is best achieved by the establishment of true form and by ensuring that the choices of a game combine into the different high level strategies you want to offer players.

Conclusion

Designing a game is akin to composing a song: we define the winning plays and their variations like a musical score sets a theme and its evolution. These structures need to be respected by the performer (player or musician), but also allow for some improvisation on the norm. We’ve proposed a series of principles for the design of gameplay and also introduced the notion of true form that describes the point of contention that emerges from the interaction of game dynamics. Lastly, we observed how structure and variability must balance one another in order to define gameplay as a meaningful possibility space. Sid Meier describes a game as “a series of interesting choices”. Looking at this quote from the perspective of structure and variation, we can say that an interesting choice is one that proposes a clear problem but where the right answer is uncertain. I believe that establishment of winning plays and true form can create structure and clarity to engage players in exploring the uncertainty of a space of possibilities.

References:

• MDA: A Formal Approach to Game Design and Game Research – R. Hunicke, M. LeBlanc & R. Zube – This research paper from 2004 proposes a framework that deals with emergence and the distinction between game elements and the resulting dynamic.
• Playing to win – David Sirlin
• Counterplay and Teamplay – Thomas Cadwell – Slides from a 2013 GDC presentation where Thomas details his concept of Counterplay that seems to apply right in a balance between structure and variation
• Building Tight Game Systems of Cause and Effect – Daniel Cook – Although he calls his principles tightness and looseness, I think we’re talking of the same things.

Just like fun, gameplay is a word that always felt awkward to me. This is critical for game designers as it is mostly their responsibility, yet there doesn’t seem to be any established definition of it. Dictionaries generally point in different directions and alternatively define gameplay as game content, game plot or as the actions of a player. Specialized literature often goes one step further by noting the emergence of gameplay and describe it as the interplay between the player and the game systems. They generally carry on by describing constitutive elements like challenge, fun and player choice to great benefit, but they always left me disarmed when asked the dreaded question: “Is the gameplay of our game fun?”. I believe that more scrutinization of gameplay as the essential part of a game would be beneficial and could help identify principles and rules that govern it and inform the process of game design.

Etymology to the rescue

To my utter dismay, in addition to being a game designer, I was also born French, and the Latin roots of my mother tongue created even more confusion as game and play translate in the same word: jeu, or juego in Spanish. Thankfully, etymology is of refreshing help as even if game and play both convey the concepts of amusement, pleasure and joy, they also show some interesting distinctions. Game tends to describe the game itself, its rules and physical form. It is also close to gammon, a term used in backgammon and that can also substitute for that game’s name. On the other hand, play is more often linked to dance, spring, act freely and typically describes the activity of participating in a game. This starts to make more sense for a designer as we understand a game as the ensemble of its rules and its physical boundaries, whether it be a game board or the lines that delimit a football field, while play is actually the actions of players within the limits of the game.

Structure and variation

So gameplay would be the alliance of structure and of variation within its boundaries? This sounds right, as the difference between a game and a toy is precisely the presence of rules that structure play in the former while the latter imposes no restriction. But it is also interesting to look at another use of the word play: The door plays on its hinges. Mechanisms require a little clearance between the teeth of cogs to function. Some freedom is needed so they can play within the structure and operate. But isn’t this the case for all structures? A political system establishes boundaries but needs to leave some freedom to its citizens or they would feel too restricted and oppose such control. The universe itself is always in flux between order and chaos and the exploration of the extremes is rather telling. One of the higher states of order of the matter is the crystalline network. The atoms in these gems are highly organized and tightly aligned while variability and freedom is almost nonexistent. On the other end of the spectrum, when structure is minimal and variation is extreme, we find particles floating in suspension, like a soup, where the Brownian movement of particles doesn’t follow any definable pattern. The commonality of these two extremes is that none of them can actually harbor life. A living cell enforces structure through its membrane and internal organization but it also allows for molecular movement or it wouldn’t function properly. The cell is in state of structured flux, just like walking is a state of sustained unbalance. Similarly, a game restricts the possible behaviours through the structure of its rules, but still allows for enough variability for the players to select their own moves. A game that is too directive wouldn’t allow for any uncertainty and wouldn’t incidentally be any fun.

Also read: Fun and uncertainty – Uncertainty is the key ingredient of fun.

Gameplay is balance between structure and variation

The universe around us is organized and the most obvious examples of it are the repetitive patterns of nature. From planets revolving and orbiting, to the tides and seasons on Earth, cycles are everywhere, and it only seems natural that living cells also had to follow the same type of timely organization with one of their most essential activities: cellular division. In his book, A Theory of Fun for Game Design (2004), Raph Koster described at length how the human brain is attuned to patterns and how this impacts the way we enjoy games. The universe is structured by patterns, cycles and rules, but they are so numerous and deeply intertwined that it is impossible for us to comprehend it as a whole. We can only understand it through deconstruction. By using abstraction, we simplify phenomena and analyze them in isolation. By removing parts of the whole to better decipher them, we turn them into symbols, we “grok” them as Koster (after Heinlein) says. Symbols are our tools to see through the maddening complexity of reality, the noise, understand its inner working, and interact with it.

Gameplay as a symbolic system

The way we create abstractions of reality is by using organized symbolic systems like language and mathematics. If we look at them from the perspective of structure and variation we can try to draw comparisons with gameplay. Firstly, symbolic systems operate under the constraints of high level principles that direct their use. Language for instance is structured by rules such as syntax and semantics. If those rules aren’t respected, and the symbolism isn’t shared, then its value becomes greatly diminished as the message will be harder to decode on the receiving end. Similarly, any mathematical reasoning must abide by the laws of logic or be totally futile. As an intellectual construction, we can define our own governing principles to structure the functioning of our symbolic system and shape the domain of abstraction we want to work in. For instance, Euclid stated for his geometry a series of axioms that he based his study on. He could then prove a series of theorems that derived from them. But geometries based on different axioms are possible. Change the initial postulates, change the shape of the abstraction, and you will be able to develop different theorems that function within this new system. This is akin to the difference between different programming languages, they all define a rigid framework, each with its specific function. Music functions in the same way as each musical genre defines its own harmonic scale. At the highest level, symbolic systems rely on the definition of structuring principles. They shape and organize the resulting space of abstraction, as the modification of those rules transforms the symbolic tool as well as its field of application.

Furthermore, the actual content that we create when we use these symbolic systems is akin to defining more explicit norms. A program defines how a computer is to behave, a sentence is generally codified to enforce a specific meaning to be transmitted, a melody is one fixed series of notes among all the options allowed by a given harmonic scale. These gems of meaning are ordered elements in the vast space of possibility shaped by the high level principles. Symbolic systems are organized as a layered alternation of normative principles that define a space of possible options, variation within the structure.

Reaction to harmonic tension

Lastly, it is also notable that symbolic systems allow for norm-bending. Poetry, for example, can twist the conventions of language and play with its rigid limits. Similarly, musicians can be expressive in how they work with harmony as they can follow it exactly by using a major scale, or stray slightly away from the established norm by using a minor scale. Harmonic modulation, or the slight modification of the tonal key, induces a harmonic tension that finds resolution as the tune goes back to consonance. Again, structured play demonstrates balance between structure and variation, the establishment of norms and sometimes their challenge.

Games appear to me in a very similar fashion. The rules become the norms that restrict player behaviour, but should also give him enough leeway for him to express choices and actually learn about the problem he is facing through interaction. These restrictions are not so much limitative but instead propose abstracted problems to offer a clear challenge and allow players to learn to provide adapted solutions. Gameplay is the result of that norm that structures the variations in player behaviour. This leads me to propose this definition.

Gameplay: A symbolic representation of a problem that structures a space of possibilities to allow for the research and evaluation of solutions.

But if gameplay shares the same functional basis as these other symbolic structures that define local norms while respecting their own intrinsic rules and principles, it might mean that gameplay also comes with its own set of meta-principles that would actually help us design games! This is what we’ll explore in the second part of this article.

Also read: Understanding Gameplay – Part Two: Technique – Learn how to use this definition to create gameplay.

References:

• A Theory of Fun – Raph Koster.  The more I get back to it, the more I feel like I’m just paraphrasing this book. Oh well, I guess we’re in good company anyways.
• Fundamentals of Game Design – Ernest Adams. Speaking of good company…
• Fun and uncertainty – Another article from this blog.

The GDC Vault has recently released Professor Brian Moriarty’s talk from the 2012 conference, Lehr und Kunst mit Perlenspiel, that reports on the game design course he has been giving at the Worchester Polytechnic Institute.

The focus of Brian Moriarty, known for his early work on adventure games at Infocom and Lucasarts, is to enable his students to “express game ideas in code”, and he developed a simple game engine to do so: the Perlenspiel. An engine without pipeline and assets, so simple in fact that it would allow his students coming from all different disciplines to each complete 6 interactive pieces within the 7 weeks of his class. Having been involved myself in teaching game design to students, I must say that I found the method that Moriarty used very interesting as the use of an engine that would keep their work abstract and away from asset building made sure they were concentrated on game rules as well as the creation of gameplay.

I would recommend this talk to anyone interested in learning or teaching game design. Also please note that Moriarty’s gameclavier Perlenspiel is open source and freely available.

Some links:

• The Perlenspiel opensource engine: http://www.perlenspiel.org/
• Biran Moriarty’s GDC 2012 talk: http://www.gdcvault.com/play/1015620/Lehr-und-Kunst-mit
• Gamasutra’s article on the topic: Link

Have you found the fun yet? is a question we often hear asked to designers. It shows how shallow is our understanding of the craft of games, but also how easily we accept such a vague mandate. Trying to help the fine folks at Relic to develop a better acquaintance with that elusive concept led me to some interesting finding that I want to share with you with the hope that it will make the designer job more focused and that it will help those that manage them provide guidance and evaluate the results.

The first step on that road was when I stumbled upon “Fun systematically”, a paper from Alan Dix that recounts his efforts with Masitah Ghazali to explore the boundaries between engagement and fun. They focused on experiences that were neither fun nor engaging – in the boring zone – and used the technique of mutation to figure out what ingredient to add to turn a boring experience into a fun one, without it becoming engaging. Their example is the pretty boring activity of waiting for a kettle to boil. Dix found out that adding the surprise effect of a bird that pops up and sings when the kettle boils brings fun to the activity. It actually seemed pretty obvious, uncertainty was the key ingredient.

Alan Dix’ mutation process to create fun

Surprise would bring playful excitement to an experience. Later on, a report came out of Starcraft 2’s Dustin Browder saying that they had decided to keep the infamous “six-pool” tactic – putting all your resources into the cheapest attack units to quickly overrun your opponent before he can develop – because the uncertainty it brought created a fun experience. That encouraged me to explore the idea of uncertainty as a source of fun and this is how that journey went for me.

Fun lives in uncertainty

Let’s first analyze the fun that comes from the great game of Tic-tac-toe. In turn, the game asks players a question: Where do you want to play your mark? The lack of certainty on which move is the best is what creates intense trepidation and fun, at least for young children. Of course there are so few meaningful possibilities that after a few rounds, it is possible to basically decode the whole game and understand the dominant strategy and the optimal counter. Interestingly, the moment you realize the whole game is known and there are no ways to trick or be tricked, the game ceases to be fun and you move on to another activity. One could advocate that you might want to keep playing to enjoy winning over an opponent that hasn’t fully understood game, but I would actually say that this is pleasure that you would be after, and not fun (see Pleasure without learning leads to addiction for more on the distinction). As we will see later on, enjoyment can come from a stable state and one can find pleasurable an easy-going activity, but as it implies learning and development, fun requires an active attitude of seeking and confronting challenge.

Also read: Pleasure without learning leads to addiction – Learning is the distinction between pleasure and fun.

The need for uncertainty is obvious in the case of abstract games with discrete states, but I believe that its appeal also translates into analog activities. Think of the evolution of fun as you learn how to ride a bicycle. The first few strides on a bike are mainly about getting used to the overall experience, everything is new and unknown, the discovery maximum: Speed, inertia, the wind on your face, the different movements and muscles involved … As soon as you master your ride enough not to be in danger, the experience is fun. Then you start controlling your ride better, and as you do, the excitement starts dropping. This is usually the moment your stab wheels are removed. That new level of complexity renews the experience and you are now enjoying the challenge of balancing your ride. But as you start to master these new conditions and exit the challenging zone, your bicycle stops being a challenge to use, and it starts becoming a boring mean of transportation. As you master its instability, it ceases to represent uncertainty and thus ceases to be fun. As further proof, common behaviors to make it fun again from that stage of mastery can be increasing speed out of your comfort zone, standing on the frame of your bike to make balance harder to control, or breaking abruptly to drift.

The low level analysis of this phenomenon is an interruption of adherence as a result of a turn. I consider the fun of it to come from the sudden change of behavior of my bike as it starts to skid with a slight incertitude on when the bike will resume adherence and change back to its normal physics. At the atomistic level, there is a sudden change in behavior, with uncertainty on when it will revert back to normal.

Actually, drifting is a perfect illustration of uncertainty applied to platformers like Super Mario Bros., as an expression of inertia. This game is all about controlling your Italian plumber through an obstacle course. There is a main problem though, as the physics of Mario make it hard to control. You don’t reach top speed immediately, you can’t stop on the spot neither, even worse is your airborne control as you try to steer in mid-air. In these conditions, evaluating the speed and timing to perform your jumps across deadly pit is uncertain, which is also why they are fun. The core activity in a game must be challenging if you want it to be fun.

The common adage is that you want controls to be tight, but I would actually advocate that in these precise circumstances, you want them to be loose, enough that they produce consistent but hard to predict results of.

Flow is a stationary state, while fun is dynamic

The idea of balancing challenge and skill is quite reminiscent of Csikszentmihalyi’s theory of Flow, except that this concept is particularly suited to describe a state of total immersion in a given task, leading to optimal and effortless results in its accomplishment. Of course if the subject is actually doing work, then you want him to be in a stable state of balance between the difficulty of his task and his skill level. That way, his concentration is maximal, his perception of time diminishes and he’s likely to go through his assignment quickly and efficiently. On the contrary, for a game experience to be fun, it requires highs and lows in the perception of challenge, as that’s the best way to acknowledge one’s progression in skill and thus alternate between the process of increasing them, and the actual enjoyment of the acquired capacities.

Flow (left) is adapted to task completion and thus requires stability, while Fun (right) is in the realm of entertainment and is experienced when on the fringe of comfort.

Csikszentmihalyi defines the “flow channel” by the zone where the skills are adapted to the challenge. If we agree that fun is experienced when exploring uncertainty and learning from it, then we need to consider the upper fringe of the flow channel, where anxiety appears, to be the zone where fun can be experienced. As players get at ease under increased challenge, their skills increase and they go back in their comfort zone. They may actually ride the flow channel, enjoying their new acquired mastery. But as this feeling gradually dissipates, they might exit the flow channel by the bottom and enter the boring zone where they don’t feel challenged enough. This is where an adventurous player may then consider upping the ante and go after more complex challenges, or if he feels like it’s not worth the effort or if new accomplishments don’t seem available, the player might decide to quit playing all together. A more competitive player will probably rarely indulge back to the boring zone and seek one challenge after another, but the main idea is that while flow is about remaining in the balance zone, the seeking fun is a more dynamic back and forth that aims at the fringe of the flow channel.

The exploration of uncertainty is at the core of all entertainment

Everyone doesn’t immediately relate to the research of challenge as describing how they seek fun. This is mainly due to the fact that we tend to associate challenge with left-brain activities like math, logic or puzzle-solving while there are many different ways to challenge ourselves and enjoy progression. As Nicole Lazzaro and Richard Bartle explain, there are different reasons why we play games, different ways to enjoy them, which leads to different player types. Let me tag in my personal buddy on that field: French sociologist and philosopher Roger Caillois. In his book “Man, play and games”, he broke down games in four core principles based on what people would seek in them. With chess as its epitome, Agon is about confrontation where you try to overcome a challenge based on your skills. Alea is the characteristic of games that rely on luck, like roulette. Illix comes from activities that would be sought after because they blur the perceptions and create vertigo, like roller-coasters. Finally, Mimicry is the roleplay or imitation of other characters or behaviors. Games can include elements of one or multiple of these categories, but it’s important to realize that they all require uncertainty to function as part of a game.

Roger Caillois’ four core game types

Uncertainty about the outcome of a game are obviously required for Agon and Alea-based games. The enjoyment of Illix is intrinsically related to uncertainty through randomness. Even Mimicry requires the uncertainty of challenge to be interesting. Roleplaying yourself or your twin brother won’t be entertaining, and as you increase your acting proficiency, you might want to try roles that are more and more alien to you, similarly to successful actors that go for more risky parts later in their career.

Clearly, in games, it’s the uncertainty that makes the experience fun. A game gives you a problem that has to bear uncertainty in how to solve it whatever the nature of the skills involved. I also believe that the concept of uncertainty being at the core of fun also applies to other forms of entertainment. A good joke for example sets a pattern for your brain to follow, and then tricks you where you weren’t expecting it. As the punch line breaks context, your brain looses traction and spins helplessly before finally “getting it”. Same thing with a story, if everything is clear from the get go, and the plot never twists, you’re in for a pretty blend experience. Instead, most stories actually create expectation of troubled resolution by establishing clearly tense situations that have change and transformation written all over. I don’t know much about writing, but I think that as long as it stays coherent, the more unexpected the resolution, the more entertaining the story.

So as a conclusion…

Someone recently called fun “boring”, but I think even worse of it. Fun is dangerous. It is dangerous to use as a mandate as it is so undefined that it is bound to lead to hit and miss that generally ends up in endless reworks involving whole teams in devastating time crunches. It needs instead to be analyzed and described as clearly as possible before moving too far into production.

So, understanding the fact that different people might have different motivations to play games I would propose the following statement.

Fun is the desired exploration of uncertainty.

We need to offer a type of exploration that will suit our audience, and define what uncertainty will be offered. I admit that it is not much, but I hope it at least helps focussing the discussion and will be the springboard for the next piece where we will analyse how to trace these paths through uncertainty, the creation of gameplay.

Also read: Understanding Gameplay – Part Two: Technique – How to apply this approach to creating gameplay.

References:

1. Alan Dix and Masitah Ghazali, Fun systematically, link
2. Mihaly Csikszentmihalyi, Flow: The Psychology of Optimal Experience
3. Nicole Lazzaro, Chasing wonder and the future of engagement, link
4. Richard Bartle, Hearts, clubs, diamonds, spades: Players who suit MUDs, link
5. Roger Caillois, Man, play and games
6. Neils Clark, Fun is boring, link

Our industry tends to use many terms without having strong understanding of them. Pleasure, motivation and addiction are generally mixed up and misused despite being central to entertainment. So much so that the generation of pleasure seems to be the main and only objective of many recent games, to the expense of challenge, and that being addictive is often considered a desired trait for a game. Gasp!

In this article, I want to use the standpoint of biology to advocate that the key goal of play is personal development, pleasure only being a consequence of it. In addition, I will show that pleasure without learning only creates an empty experience that can be dangerously addictive.

Let’s first debunk a very common confusion by establishing a distinction between fun and pleasure. Pleasurable experiences like eating a good tasting cake aren’t necessarily fun. On the other hand, I think we can admit that everything that is fun is pleasurable. It means that fun is a subset of pleasure and that’s the reason I want to focus on exploring the notion of pleasure.

Pleasure is a positive mental state that is the result of electrical stimulation of certain parts of the brain. That stimulation is typically generated by cell receptors after activation by their neurotransmitters, mainly dopamine and different types of endorphins. The actual biochemistry is irrelevant to us except to know that you can bypass the proper triggers of it and still obtain the stimulation of the pleasure centers. This can be done by using replacement molecules that trigger receptors or amplify the effect of native neurotransmitters. These are actually called psychotropic drugs and affect our central nervous system’s ability to perceive and compute information. Of course induced altered states like being tipsy or plain drunk might seem like a good source of “fun”, but let me hold that thought for now and keep on with the actual discussion on pleasure.

Pleasure is a positive mental state that is the result of electrical stimulation of certain parts of the brain.

Since it can be “forged”, pleasure on its own has limited value. A famous experiment had monkeys pleasure centers wired so they could activate them at will which led them to constantly push that button and totally ignore to feed themselves, to their ultimate demise. A freely accessible pleasure source can be dangerous and even plain lethal as everything else ceases to represent any interest. This is a good illustration that living beings are complex systems that function in their own environment but are prone to collapse if a modification that they are not adapted to is introduced and that one part of the system gets singled out.

Now that we’ve reviewed the mechanisms of pleasure and its limits, let’s try to discuss the possible role for pleasure. Biology considers pleasure as an adaptation mechanism for evolved animals. All living cells can be modified as they split, due to errors in the replication of their genetic code. This is how different traits appear in species and allow mutated individuals to survive evolutionary pressure. Typically, natural selection is rather a negative type of filtering that eliminates all individuals that can’t survive a change of conditions like the presence of antibiotics if you are a bacteria, the disappearance of low-hanging leaves if you are an small herbivore, or a giant asteroid hitting your planet if you are an ecosystem-dominating razor-teethed dinosaur. Because of how often unicellular organisms can reproduce and how simple their DNA is, they are way more likely to develop different traits and thus be ready to survive environment changes. More evolved organisms like mammals have to wait for sexual maturity to reproduce and mix their DNA to create offspring. Evolved species DNA is so complex though, that traits are dependent on multiple genes, making new traits way rarer to appear. This is where pleasure comes into play (no pun intended).

As we saw, pleasure can be an absolute motivator, so if an individual’s brain is wired to give us pleasure in response to a behavior that makes him more fit, this will encourage him to engage in the related activity and help his survival. For example, our brain releases dopamine when we understand something which obviously plays a role in the fact that humans are actually quite smart. Our body generates endorphins after a physical exercise, giving us the post-workout high which motivates us to train again and build more muscle. More interestingly for us, and like most evolved animals, we also trigger pleasure when we play.

If pleasure is linked to positive behaviors, it becomes a positive feedback loop for development

It is as if, in nature, the balancing element of pleasure is the effort required to obtain it, thus indicating that the true role of it is to motivate evolved animals to engage in activities that will fulfill their needs. Arguably, humans have needs of different types: Physical, emotional, spiritual, social and intellectual. Video games have historically represented a physical challenge with focus on hand-eye coordination and naturally grew into the intellectual sphere by including strategy and puzzles. With more focus on narrative, they started touching on emotions and spirituality, and with the development of multiplayer we are also expanding to social, giving them a pretty good potential as personal development tools.

Conditioning makes our brain fire up with excitement, but is it meaningful?

But unless they somehow deliver a learning experience they can become a pleasurable but mind-numbing grind that leaves you feeling empty. That type of game that provides pleasure and can be played without effort and thus without limit, I call addictive. It is the type of entertainment that tricks our body and brain to focus on meaningless glitter and look for the next release of dopamine. Pleasure itself is the only currency promoted and the participants pretty much end up like the monkeys in the aforementioned experiment.

The function of games is not to give us pleasure as this is only the consequence that motivates us to engage in it. Instead, the value of games is to learn, challenge or develop ourselves in situations that real life wouldn’t allow. If we let ourselves go only after pleasure, we just create a perverted and hedonistic system that doesn’t provide any benefit and instead establishes such a short and easy loop to pleasure that becomes addictive and ultimately destructive to your body, mind and soul.

Some links:

• The role of pleasure in evolution and how it can be turned into addiction – How cocaine turns users into addicts
• “By definition, we are the biological descendants of the tribes who told stories to survive.” – Into the woods: A Practical Guide to the Hero’s Journey
• Psychology applied to reward systems – A look at the behavioral psychology of random loot

You probably heard of game theory at one point, nodded your head trying to convince the people around you that you knew what it was about, but like me, struggled to grasp its applications to actual game design.

Game theory is a field of mathematics that studies the outcome of complex games, looking for points of equilibrium, value of different strategies through the payoff resulting from the different choices available. It must certainly be interesting on its own, but is most generally applied to concrete situations like politics, economics, sociology, competitive gaming and thermonuclear warfare.

I am not going to try my scholar impersonation and try to outdo proper definitions like wikipedia’s.You should probably read their article if you want a good introduction.

The immediate value of learning about game theory is to hear about the terms of zero-sum or non-zero-sum games, games with complete (like chess) or incomplete information (like Starcraft), the concept of decision tree and the different tools to model and analyze games as well as the famous prisoner’s dilemma. Not only this nomenclature will allow you to consider games in a more abstract fashion and to better categorize and analyze them, but it can also help you discuss them with fellow designers that would share the same knowledge.

Past this, I must admit that most of my efforts to dig deeper into game theory have left me with a feeling of lack of adequation to game design, probably because our craft is so young, or because my own understanding of it is too limited. The books I could lay my hands on weren’t really written with game design in mind and I couldn’t learn in a satisfactory fashion, but I know about ways to learn about game theory in a way that is relevant to game design, and that’s what I want to share with you today.

To me, game theory applied to game design is: The science of establishing optimal play in a complex game situation. In this perspective, it is more about understanding a player’s process when he is trying to make the best move. It impacts design in an indirect fashion, but it is still a way to inform it.

The key methods that game theory uses are based on the systematic listing of the different options and their respective payoff, in a matrix or in a tree, depending on the game itself. Way before I heard about game theory, I had used these methods in two contexts. The first was when trying to solve the logic riddles of Raymond Smullyan’s book “What is the title of this book?”. In it, the reader is taken through riddles about the inhabitants of a strange island, that are either knights and speak only the truth, or knaves that always lie. One of the very first problem goes as such:

According to this old problem, three of the inhabitants -A, B, and C- were standing together in a garden. A stranger passed by and asked A, “Are you a knight or a knave?” A answered, but rather indistinctly, so the stranger could not make out what he said. The stranger than asked B,  What did A say?” B replied, “A said that he is a knave.” At this point the third man, C, said, “Don’t believe B; he is lying!”

The question is, what are B and C?

So, let’s evaluate B’s statement, exploring the possibility that he would be right. Then that would mean that A would have said he was a knave, which is impossible as if he was lying, he would be a knight and would have lied, and if he was saying the truth and was thus a knight we would experience a paradox and all life as you know it would stop instantaneously and every molecule in your body would explode at the speed of light, which would be bad.

We can then safely conclude that B is a liar, thus a knave.

The evaluation of C’s statement “Don’t believe B; he is lying” concludes of course that he is a knight.

Now you might say that this is not truely game theory, and you would probably be right, but the fact is that the logic and systematic approach are the same than those used in game theory and are adapted when evaluating a game position. It also relates to how game theory applies to player undestanding as we are trying here to find the solution to a problem, “win the game” as you could say, which segways into the other way to learn game theory related skills: Competitive gaming.

Playing a game to win is akin to what we just did, solving Smullyan’s riddle. We evaluated all the different possibilities in order to find the best one. This is actually the same process you go through, consciously or not, when you try to select the best option when playing a game. The more competitive one becomes, the more he thinks about the different choices and tries to establish an optimal strategy. Competitive street fighter player and professional designer David Sirlin describes this behavior in his book “Playing to Win”.

A competitive game, to me, is a debate. You argue your points with your opponent, and he argues his. “I think this series of moves is optimal,” you say, and he retorts, “Not when you take this into account.” Debates in real life are highly subjective, but in games we can be absolutely sure who the winner is.

Now trying to engage in competitive play yourself might be quite a daunting task, and actually quite unnecessary. Just like car engineers don’t need to be Formula One champions, actual high skill level in playing games is overrated when designing them. Instead, understanding how top players function and what attracts them to specific games will help you design games that have depth and can hold the test of time. Once again, designing games is informed only indirectly by the actual practice of games. That’s where Sirlin’s book can help you get an insight into competitive behavior. On a similar note, thanks to the recent development of e-sports and streaming sites, you can also find many web show about the different competitive games. Listening to their analysis really helped me understand the depth of these games. I would recommend the Day[9] daily as a first foray into competitive gaming.

There you go, I hope these pieces of advice motivated you to dig a bit into game theory!

Related links:

• Wikipedia’s entry on Game Theory
• David Sirlin’s website
• The Day[9] Daily