Abstract

NOTE: This is a translation from an article that I wrote and was published by Ludology, the first Chilean magazine about game design, publishing articles by the likes of Marc Albinet (Assassin’s Creed) and Richard Bartle (MUD1, “Designing Virtual Worlds”).

The following text aims to analyze the influence of real-world systems on videogames and how using them allow designers to create games that are meaningful, engaging and allow players to develop skills that they can use outside of the game’s context. In addition, methods that help analyze and modify real-world systems are explained specifically in the context of game design.

1. Systems Design

1.1 The Connection between Real Life and Games

Games have always been strongly connected to human condition. The game arises from early childhood and is maintained through the whole life of human beings (and many animals too). Historically, games have been used as an entertainment, a safe space in which players can try to dominate the system of the game through different means, some that they will never use in real life or that they will never be in the need of using them.

Given this safe space guarantee is that many game designers have explored deeper topics taking for example games like “Celeste”, “Papers, Please” or “This War of Mine”, just to name a few. All these games have in common that they grant players a safe space of action in which they can make different decisions to explore moral limits. This, in turn, allows them to explore pretty differentiated systems but that are highly connected with each other, like for example saving an older teacher in “This War of Mine” does not report any benefit to the player, on the contrary, it has a negative impact on the resources of the player. But not helping the old teacher can affect the moral system of the characters, and why not, the player’s moral system too.

1.2 What is Systems Thinking?

Systems Thinking is a way to look at the world around us different from the reductionist way of looking at it that many “educational” institutions have fostered around the world (Meadows, 2008). Systems Thinking helps us analyze and come up with models of the different parts that compose systems and how these parts interact with each other. More importantly, Systems Thinking allows us to identify the goal of the system.

This way of thinking promotes the consideration of the world in an holistic way, considering most or all factors that influence it, to go digging deeper and deeper to the lowest-levels of the system. According to Donella Meadows, one of the objectives of systems thinking is to foment systems that create stability and resilience instead of just productivity, because productivity alone can destabilize a system beyond the reconstruction level.

1.3 Systems Thinking in the 21st Century

Even though systems thinking has been used since the beginning of the 20th century mainly by mathematicians and engineers, it’s not until the 80’s that systems thinking started to be in vogue, being used to solve problems not only in maths and engineering, but also to analyze and solve social and ecological problems. Systems Thinking has helped to analyze complex problems that in any other way would have been almost impossible to analyze because of the amounts of parts and connections, like global warming or the limits to human population growth.

Generating models and simulations of these systems, taking into consideration the subsystems that compose each one and the connections between them can help us predict the behavior of each system and how it will react to changes that can be applied to improve the performance of it.

1.4 The Relationship Between Game Design and Systems Thinking

Following its expansion through a range of human affairs, systems thinking started to be used to design games, known as “systemic games”. Games, in their logical base, are formed by systems. But even though all games are systems, not all games are considered systemic based on how players make decisions and how these decisions influence the behavior of the system. Systemic games are different to non-systemic games in that the former include systems that are represented in the game area, from which players can explore different configurations to understand and dominate the system to their favor. It’s because of this feature that systemic games usually have numeric representations (sometimes called parameters) of certains game elements.

Because of the clear connection between real-world and games, the first systemic games were based on omnipresent systems in human life, like war, economics, business administration or city management, using conventions from the Strategy, RPG and Simulation genres. Today, most systemic games include RPG elements because this genre is one of the wider in terms of available personalization of individual elements and the ability to evolve and advance using different means to the same end. Likewise, most systemic games lack a predefined story or narrative, because it spurs naturally from the interaction of the player with the system of the game (Sellers, 2018). Games like “Civilization” or “Offworld Trading Company” have a very thin narrative, but anyways they find a way to generate stories that are remembered fondly by players. Despite this lack of a specific narrative could lead to unconvincing arguments or situations, the player-made stories by using the system generate a strong emotional response, even when they are sometimes unforeseen by the game designer.

2. Systems elements in Video Games

In systems Thinking there are 3 common patterns that can be identified: Economies, Ecologies and Engines (Sellers, 2018). The economies are composed of Reinforcing Feedback Loops, a type of loop that constantly diminish or increase itself each time it feeds back. Ecologies tend to a balance point using Balancing Feedback Loops. Much like ecologies in the real world, they can only balance themselves inside a certain range. Engines mix Economies and Ecologies while also using other elements that convert or trade resources inside the system, like real engines transforming one type of energy into another.

2.1 Economic Patterns

Economic patterns, as the name suggests, emulate the economic systems so players can earn resources that they can invest to collect or produce even more resources. Resources flow circularly until they are eliminated from the system based on the macroeconomic system (Castronova y Lehdonvirta, 2014). Economical systems also work the other way around, so players that don’t have enough resources can’t invest generally that makes them lose their resources until they are excluded from it. This effect is known as the “Matthew Effect” based on a Bible verse in the Matthew gospel that can be summarized in the context of Economics as the rich get richer, the poor get poorer. This metaphor has been used to explain how most economies work, multiplying the resources of the ones that already have and diminishing the resources of the ones that don’t have exponentially.

Real-world economy systems have been widely replicated in video games. From the very famous “Monopoly” and its predecessor “Landlord’s Game” by Elizabeth Magie all the way to city-building simulators like “Simcity” or “Cities: Skylines” and war games like “Total War” or trading systems like “Offworld Trading Company”, that have used the different sides of the economical systems.

There are also games that have explored economic systems using a one person perspective instead of a god-like perspective. RPG games allow players to acquire resources that can be invested in better equipment or powers, therefore increasing the likelihood of obtaining even more resources.

All these systems have two elements in common: 

• All of them are based on the player obtaining resources and investing them in ways to obtain even more resources and,
• They have elements of buying and selling systems based (sometimes loosely) on supply and demand generating (again, sometimes loosely) inflation or deflation of the system’s resources.

A classic economic system consists on obtain a resource (for example money obtained through work) and then use it (investment) to earn even more of that resource.

2.2 Ecological Systems

Ecological patterns on the other way are based on Balancing Feedback Loops, so, instead of infinitely reinforcing their behavior like economies, they tend to a balance point. Ecological patterns are present in all games in one way or another, because there is always an opposition that creates challenges for the players. The game designer is the one that needs to balance the situations and more generally the systems to create challenging situations for players.

Ecologies can be destabilized outside their resilience point therefore becoming brittle. When they are in this state, it could be impossible for the system to function again. In games, brittle systems can be seen opposing players for example taking or giving them more resources, resulting in losing or winning the game correspondingly. If this unbalance that leads to one of these two states is perceived as unfair or is lacking feedback, it could lead players to frustration or boredom states. 

Because Ecologies tend to a balance point they are perceived as more static than Economies. This sometimes results in lack of players’ agency and restricted interaction with the system. This could be the reason why literal representation of ecologies tend to not share the same success as Economies, because when ecologies are in balance, there is not much to do for the player. Ecologies in games tend to be a complement of Economies and they are usually used to create opposition and challenge for players.

A typical ecology based on the predator-prey system. Both populations get to a point of equilibrium based on seasons, which maintain the stability of the system. Introducing a new predator could unbalance the system.

2.3 Engines

Engines are combinations of Reinforcing and Balancing feedback loops, adding two more functions: Traders and Converters. They are essentially the same because both take resources from the players and give them other resources in return. The difference is that traders keep the traded resources in the systems, but converters effectively use those resources to create new ones. In real life though, converters usually generate leftovers that when not taken into account, generate contamination and other problems that destabilize the system. In games this is usually not a concern, but this new understanding of the world opens opportunities to include such elements in games.

“Games are engines of emotions” wrote Tynan Sylvester (2014), a brief but precise definition because games are in its whole formed by many engines interacting with each other. The connections between these engines generate systems and subsystems and deliver an emotional experience to players. Understanding games as experiences that deliver emotions help designers to focus on these engines and their connections, using them to deliver the desired experience, namely, the goal of the system.

“Offworld Trading Company” is a game that is based on a series of different engines. Unlike other PvE RTS games, the game is based on a supply and demand economy that depends on the player taking a resource and converting it into another using another building.

A cascade resource-tree generates resources that can be sold for more money.

2.3 Maslow’s Pyramid

Real-world systems are usually created to fulfill a human need. In the case of natural systems, humans have adapted or destroyed the system or parts of it. So, human needs are so powerful that humans are sometimes willing to make harmful decisions in the long-term to satisfy an apparent necessity in the short-term. An useful scheme to analyze human needs is the one proposed by Maslow known as the Maslow’s pyramid or Maslow’s hierarchy of needs (1943), in which human needs are divided into 5 hierarchical groups: Physiological, Security, Belonging, Esteem and Self-actualization needs. According to this hierarchy, people will not look for higher needs if lower ones are not fulfilled.

Is essential to consider Maslow’s hierarchy of needs both inside and outside the game. Outside the game, this is, player needs are usually on the top three groups of the hierarchy, being the most common self-actualization. The challenge posed to players allows them to unleash their creativity and exploration in order to understand and dominate the system, while also fostering a problem-solving attitude and sometimes, considering moral and cultural affairs. Other players, can be argued, enter because of the need of being recognized, like many professional players or speedrunners, that want to be recognized by being in the top step. This can be translated to players competing in an online game that uses leaderboards.

Inside of what is known as the magic circle, namely what is happening inside the game, games tend to explore all types of hierarchies, being the most successful ones that use the lower steps of Maslow’s pyramid. Many action-packed games are based on survival, using death as the end game. Other games explore many hierarchies within it. For example in ”Minecraft”, players start fulfilling physiological needs like shelter or food. Then, as the game progresses and the player becomes more familiar with the system of the game, players look for higher needs, like using red-stone to create musical instruments or improve home aesthetics. The search for higher meaning when the resources are present are rewarded by new ways to solve problems and a higher sense of meaning.

Other games remain in one or two hierarchies.“Frostpunk” puts players in a position when they are always fighting against the clock and the environment, with little time to be worried about the beauty of their city. Puzzle games like “The Witness” don’t put the player in any danger, so they can focus all their efforts in solving the puzzles of the games and look at things in new ways to discover hidden secrets.

3. Methods to Design Engines Based on Real-World Systems

As already mentioned, games can use and replicate real-world systems. This has diversified advantages. One of them is that due to the fact that the player most likely already knows the real-world system, it will take less time to learn and understand the system of the game. On the other side, the real world is fairly challenging and unpredictable by itself, posing problems that we have to solve many times without the knowledge of all the influencing factors, but also without the real-world consequences. Games grant an exploration space free of consequences in which the players are invited to try different avenues to solve a problem without real harm. In this way, games can prepare players to make better decisions in the real world and improve their decision-making ability. To create this type of stems, the designer must use methods that ensure the successful analysis and implementation of the real-world system into the game, in order to create more interesting and meaningful games.

3.1 Abstraction

The abstraction process is fundamental to design game systems based on real-world systems. Scientific simulations are based on precision, while game simulations are based on clarity, as Chris Crawford suggests (2003). To know which of the parts of the system to represent in the game we can use abstraction. This process consists of analyzing the real-world system to simplify or eliminate systems and subsystems so as to represent or give control to the player of the ones that support the desired experience.

To have a better idea of which systems to represent and to give control to the player, the designer can start by asking the following:
What is the system objective?
What subsystems support that objective?
Which of these subsystems can be automatized or eliminated without changing the objective of the system?
Which of these subsystems require more interaction/decisions/input to work?
Having the answer to these questions will greatly facilitate the implementation of those systems and will lead to a more smooth and clear design process, laying good foundations to begin the design of the game with a clear objective that supports the desired experience.

3.2 Emergence and Complexity

Another characteristic of systemic games is that they generate what is known as emergence and complexity. Emergence refers to the system displaying emergent behaviors, this is, certain behaviors are generated from the lowest levels of the system towards the upper levels, what is known as a bottom-up behavior. These behaviors generate combinations that the designer didn’t directly implement in the game, rather the designer created the systems and connections between them that allow the player to explore new uses and combinations of those systems and connections. This encourages players’ creativity through the use of new and personalized methods to pursue their objectives.
A simple system is a system where parts are not connected between them. A complicated system is one in which there is no feedback, rather it has only linear connections. Both simple and complicated systems by their own nature can’t generate emergence or systemic behaviors. On the other hand, complex systems generate connections and feedback interactions between the systems. To clarify, this doesn’t mean that a complicated system is composed of hundreds or thousands of parts (but it can). It means that parts are connected between them, generating the already discussed Economic, Ecologic and Engine patterns.

Strategy games like “Starcraft” or “XCOM” have strongly interconnected systems that allow players to use different strategies to overcome the same obstacle. To exemplify, in “Starcraft”, players can choose different strategies on how to group their units and in which positions of the battlefield these units will be placed. A similar behavior can be seen in “XCOM”, where players can use different combinations of classes and individual soldiers to make their way along the map and complete the level objective. It’s important to notice though that the behaviors of complex systems are much more difficult to predict thus many systemic games are prone to balance problems.

3.3. Engines Analysis and Modification

No, I’m not saying that disassembling your car will make you a better game designer. I’m referring to one of the most important abilities for every game designer, that is, the capacity to analyze mechanics, dynamics and aesthetics on existing games to adapt and modify them to use them in their games.

Not a single game (and not a single piece of art) has born out of nowhere. All games are designed by people that are inspired by previous games but also by their own life experiences. The designer must be able to consciously understand what parts and systems generate a desired experience (aesthetic) and most importantly why (or why not) this is. A useful technique to understand and analyze systems is to create graphic representations of the system, known in systems thinking and “models”. These models can represent different levels of the system and can be separated into a few models for more clarity when thinking and presenting these models.

To modify systems, a more reflexive, iterative process is needed in which the designer must balance the systemic aspects of the real-world system that must be adapted to support the main experience. It is important to note that modifying different aspects of the system leads to bigger or lesser impact, depending on which element is being modified. To have a clear understanding of the hierarchies of importance when modifying a systems, it comes handy to use Donella Meadows (2008) list of Leverage Points.

9. Constants, parameters, numbers (subsidies, taxes, standards).
8. Regulating negative feedback loops.
7. Driving positive feedback loops.
6. Material flows and nodes of material intersection.
5. Information flows.
4. The rules of the system (incentives, punishments, constraints).
3. The distribution of power over the rules of the system.
2. The goals of the system.
1. The mindset or paradigm out of which the system — its goals, power structure, rules, its culture — arises.

You can find the link here to view a full article explaining why these leverage points work that way, along with an updated, revised list (that I didn’t find too much useful to game design, but it could be useful to you).

2.3 Maslow’s Pyramid

Real-world systems are usually created to fulfill a human need. In the case of natural systems, humans have adapted or destroyed the system or parts of it. So, human needs are so powerful that humans are sometimes willing to make harmful decisions in the long-term to satisfy an apparent necessity in the short-term. An useful scheme to analyze human needs is the one proposed by Maslow known as the Maslow’s pyramid or Maslow’s hierarchy of needs (1943), in which human needs are divided into 5 hierarchical groups: Physiological, Security, Belonging, Esteem and Self-actualization needs. According to this hierarchy, people will not look for higher needs if lower ones are not fulfilled.

Is essential to consider Maslow’s hierarchy of needs both inside and outside the game. Outside the game, this is, player needs are usually on the top three groups of the hierarchy, being the most common self-actualization. The challenge posed to players allows them to unleash their creativity and exploration in order to understand and dominate the system, while also fostering a problem-solving attitude and sometimes, considering moral and cultural affairs. Other players, can be argued, enter because of the need of being recognized, like many professional players or speedrunners, that want to be recognized by being in the top step. This can be translated to players competing in an online game that uses leaderboards.

Inside of what is known as the magic circle, namely what is happening inside the game, games tend to explore all types of hierarchies, being the most successful ones that use the lower steps of Maslow’s pyramid. Many action-packed games are based on survival, using death as the end game. Other games explore many hierarchies within it. For example in ”Minecraft”, players start fulfilling physiological needs like shelter or food. Then, as the game progresses and the player becomes more familiar with the system of the game, players look for higher needs, like using red-stone to create musical instruments or improve home aesthetics. The search for higher meaning when the resources are present are rewarded by new ways to solve problems and a higher sense of meaning.

Other games remain in one or two hierarchies.“Frostpunk” puts players in a position when they are always fighting against the clock and the environment, with little time to be worried about the beauty of their city. Puzzle games like “The Witness” don’t put the player in any danger, so they can focus all their efforts in solving the puzzles of the games and look at things in new ways to discover hidden secrets.

Conclusion

Games have been largely used as tools to acquire skills and knowledge that can be transferable to the real world (Fiacco, 2013). The learning could not be as direct as other learning methods, but it can make players consider different points of view to solve problems that before that were not considered (Macklin, 2016). For example, Chess is far from being an accurate representation of a real battlefield, but it can develop the ability to look forward and improve the time of decision-making. Other games like “Starcraft” can be used to develop the practice to enter a state of flow, improving the ability to focus attention and concentration, while also improving decision-making under pressure.

Games are so useful to develop abilities that have been used by AI (artificial intelligence) researchers are using games to train AI to make decisions and learn abilities that can be later applied in fairly different contexts. Researchers have used “Starcraft II” to develop more independent AIs, to generate a bottom-up thinking where multiple AIs feed information and make decisions, instead of a central mastermind making all the decisions. Others have used “Minecraft” to develop AIs that can acquire knowledge by themselves, without requiring direct human input. This shows that games can be useful to develop abilities in humans (and AIs) that can be useful outside the game context. Also, both directly and indirectly, players acquire knowledge that can be useful to formal education like “Portal 2” being used to teach Physics (Gilbert, 2016) or “Crusader Kings II” used to teach medieval history.

Games, like every work of art, are inspired in the artist’s view, in this case, the designers’ views and analysis of the world. Our world is a constant source of inspiration if we stop and step back for a while, to find multiple and diverse systems that can be modified to generate emotions in the players. If game designers understand the real world from a systemic point of view, they will be able to use and abstract the elements of those systems to create a conscious desired experience that leads to more meaningful and compelling games. If the designer understands which systems, connections and parts to use and which to eliminate or automatize, the game designer can create more resilient systems that allow new content to be included in the system (updated, DLCs, reworked versions) without breaking the system.

The world is our source of inspiration, our mind and analysis capacity are our eyes and the design is our canvas to create a better world.

References

Adams, E. Dormans, J. (2012) Game Mechanics: Advanced Game Design. USA: New Riders Games.

Castronova, E., Lehdonvirta, V. (2014). Virtual Economies. USA: The MIT Press.

Crawford, C. (2003). Chris Crawford on game design.

Fiacco, L. (2013) Real world skills from video games. https://www.youtube.com/watch?v=sIPvnWZ5O6Q

Gilbert, S. (2016). Designing Gamified Systems. UK: Taylor & Francis.

Macklin, C. (2016) Playing with Complexity: Games and Systems Thinking. https://www.wildlabs.net/resources/thoughtpieces/playing-complexity-games-and-systemsthinking

Maslow, A. H. (1943). A theory of human motivation. Psychological review, 50(4), 370.

Meadows, D. (2008). Thinking in Systems: A primer. UK: Chelsea Green Publishin Co.

Sellers, Michael. (2018). Advanced Game Design: A Systems Approach. USA: Pearson Education

Temming, Maria. (2019). AI can learn real-world skills by playing video games. https://www.sciencenewsforstudents.org/article/ai-can-learn-real-world-skills-playing-videogames