Book Club: Working Stiff by Dr. Judy Melinek and T.J. Mitchell

I wanted to learn about human anatomy.

It’s a running joke in my family that we all sucked at biology in school, and dropped the subject like a hot potato as soon as we could. As I’ve become more and more interested in health and fitness, however, I found my embarrassing lack of knowledge about the human body to be a handicap.

I bought a college anatomy textbook, but found it too dense for a biology beginner. I tried watching Crash Course: Anatomy and Physiology, which was a lot more accessible, but was still a firehose of information that I struggled to fully digest. When I found myself staring blankly at the Michigan edX Anatomy course instructor writing “osseous tissue” on the screen, I decided I needed a different approach.

I needed something oriented around a story, I decided — I needed to find a story of anatomy. Maybe something about clandestine dissections of human bodies, or about how each bone and muscle was discovered and christened, or whatever. Just not a college textbook.

I went on Amazon and searched for narrative non-fiction books with a focus on anatomy. That is how I found Working Stiff by Dr. Judy Melinek and her husband T.J. Mitchell. Working Stiff is a memoir about Dr. Melinek’s two years at New York City’s Office of Chief Medical Examiner (OCME), where she learnt how to conduct autopsies and piece together the stories of the dead.

I’ve been fascinated by medical memoirs for years now, especially the “making-of-a-doctor” subgenre. Like any good genre story, there are certain tropes that appear in every making-of-a-doctor story: the bright-eyed new doctor, fresh out of medical school, sees their first patient; the new doctor who doesn’t know how to insert a cannula/suture an incision/other routine procedure and has to be taught by a nurse; the new doctor’s first code, first death, first “I’m sorry, we tried our best”; the crazy shifts that leave the new doctor falling asleep anywhere it is possible to fall asleep (on a gurney; in traffic); spousal troubles from the doctor’s gruelling workload; the shift where the young doctor is alone overnight and a patient comes in in awful shape; the case where the young doctor nearly misses a serious diagnosis; the case where the young doctor saves the day and gets a laconic utterance of praise from their attending physician; the doctor’s last month, last week, last day as a resident, before they morph into a beautiful, complete, board-certified physician or surgeon.

Well, Working Stiff is a very different kind of making-of medical memoir. The story starts with Dr. Melinek as an overworked first-year surgery resident who quits after she has to perform an appendectomy on a patient while she (Dr. Melinek, not the patient) is feverish with the flu. She switches to pathology, loves it, and her chief resident tells her to do her forensic pathology rotation in New York:

“If you really want to learn forensic pathology, do a rotation at the New York OCME,” my chief resident advised. “All kinds of great ways to die there, and the teaching is brilliant.”

That is how Dr. Melinek finds herself as a forensic pathology fellow at the NYC OCME after completing her pathology residency.

It is true that New Yorkers die in unexpected ways, although I don’t know if I would call them “great”. I'm not going to lie, though: some of the stories made me wish I were still living in that crazy city, always on the edge of adventure. Dr. Melinek tells of the time she was assigned to the “postal bin case”, when the NYPD hauled an postal bin containing a dead body to the morgue for the medical examiners to deal with. (Spoiler: homicide by heroin poisoning — yes, you read that right.) During a fight, a man is pushed into a 300 deg F steam tunnel and boils alive. (Boils dead? Boils dead alive?) A decomposed body is found on its knees with an electrical cord around its neck, and words scrawled in blood in the kitchen and on the bathroom door.

For the forensic pathologist, the focus is finding the “proximate cause of death”: the last mechanism that resulted in each person’s death. Their analysis is medical, not legal or criminal. We think of people as dying in car accidents or falls, but medical examiners think of them as dying of “acute intrathoracic aortic transection” (translation: broken aorta) or a “subdural hematoma” (translation: bleeding between the brain and the skull). I learnt some physiology that I’d never thought about. For example, medical examiners can reconstruct the order in which bullets hit a victim based on how much blood there is around each gunshot wound, because arterial pressure drops and less blood hemorrhages out of later wounds.

This is a making-of medical memoir that, by nature, turns most of the common medical tropes inside out. For doctors, as for most of us, a dead body is an ending, but for forensic pathologists, it is a starting point. Through each dead body, Dr. Melinek is able to reconstruct each person’s last moments, bringing their stories to life. Instead of the nervous meeting with the first patient, Dr. Melinek dissects her first cadaver and fails to figure out how he died; instead of a nearly-missed diagnosis, Dr. Melinek makes a mistake on a death certificate that could have sunk a homicide trial. She has victories, too: a woman with narcotics in her urine dies after a blood transfusion. Hospital doctors write the death off as narcotic-related, but Dr. Melinek’s investigation leads to the unusual (and correct) diagnosis of TRALI (transfusion-related acute lung injury), and gets a laconic utterance of praise from the chief medical examiner.

An essential component of the medical memoir is the origin story: what made the author decide to become a doctor? In this case, the story about quitting the surgery residency is mechanistic, almost like a plot device that leads to our heroine finding her calling in pathology. The real origin story that runs like an undercurrent throughout the book and gives Dr. Melinek's work purpose is the suicide of her father Menachem Melinek. The senior Melinek’s death, which happened when Judy Melinek was just 13, shapes how she thinks about her profession. Suicide is perhaps the most brutal type of death for those left behind, and Judy Melinek understands more acutely than most our need for answers from those who cannot give it.

“Taceant colloquia. Effugiat risus. Hic locus est ubi mors gaudet succurrere vitae.” I stared at the words… The security guard’s expression softened; it was clear that she had greeted a lot of stunned people walking into that building. She glanced back at the polished silver motto and said, “‘Let conversation cease. Let laughter flee. This is the place where Death delights to help the living.’”

A shadow that necessarily looms large over the story is 9/11. The book contains the level of precise detail one would expect from a forensic pathologist, including the dates of autopsies, and their proximity to September 11, 2001 is impossible to ignore. As I read, I wondered when I would get to the chapter on 9/11, and when it came near the end of the book, I was not disappointed. From the point of view of narrative structure, 9/11 is a natural climax. Nothing tops 9/11 in terms of drama, or in terms of magnifying the importance of the medical examiner’s office.

Even the 9/11 story turns a medical memoir trope on its head: it begins with one of Dr. Melinek’s friends, an oncologist who rushed to her hospital on the morning of September 11, and sat with her fellow doctors waiting for mass casualties to arrive. They didn’t.

In terms of medical complexity, 9/11 did not seem particularly interesting the way it was described in the book. There was no mystery about the cause of death. That's not to say the 9/11 story is shallow or insignificant – quite the opposite. The 9/11 chapter documents Dr. Melinek’s boots-on-the-ground perspective of a massive logistical effort to solve the mystery of how many people died in the World Trade Centre buildings, to give the bodies and bones names and to give families and friends closure. It's clear that Dr. Melinek enjoys the intellectual challenge of her work, but it is just as clear that the driving force of her work is emotional in nature. Medical examiners seek out the stories that dead bodies tell, in order to bring peace to the living.

I wanted to learn about human anatomy. Did I get what I wanted? I certainly didn’t get an anatomy textbook. I got, instead, one heck of a story about anatomy and physiology as dynamic disciplines, and a story was what I was looking for. I’ll be cherishing the experience of reading this book for a long time.

Civ VI Epic Series, Part 1: Model Thinking and the Interaction of Complex Systems, Part A

If you wanted to build a video game to model the evolution and complexity of human civilisations, how would you do it?

That is a question so broad, it is virtually impossible to answer without some kind of framework. So let’s establish one: we want a way to represent territory, something that reflects the diversity of terrain on Earth. Some terrain is better than others for farming; some terrain is better than others for mining. Hills are harder to traverse than flat land, while mountains are impassable for regular travel. We need a way to represent fresh water in the environment, because that affects human settlement patterns. We need some way to represent terrain features such as forests and jungles and swamps, because these affect the possible uses for the terrain, and they can also be removed if you wish: forests and jungles can be cleared, and swamps can be drained. As far as the sea is concerned, we need to at least make a distinction between the shallow coast, where fishermen work and where littoral brown-water navies can operate, and the deeper, treacherous ocean that is out of reach without more advanced technology. Oh — and we need some way to reflect that parts of the world are more abundant in some resources than others.

There are many ways to skin this cat, but here’s how Civ VI does it:

Click/tap to enlarge: the details are important

(Note: this image is from a True Start Location Europe map, a Civ-generated map of Europe where civilisations spawn at the location of their historical capitals. Most Civ games take place on maps that are Earth-like, but not recognisably Earth.)

The game uses hexagonal tiles, and each tile has a base terrain type and features that sit on top of that base terrain. Some tiles have resources, such as stone, fish and olives. The northern part of Italy contains a mountain range (mimicking the real-life Alps), and this mountain range includes a natural wonder, the Matterhorn.

To make this clearer, I’ve annotated some of the terrain features (white) and resources (red) on the map. The Matterhorn is marked in blue:

Click/tap to enlarge: the details are important

This is the first step in trying to model the evolution of civilisation: modelling the terrain. The next question is, how do we quantify the value of the terrain?

Yields Part I: Food, Production, Gold

In Civ, there is a game concept known as tile yield. The yield refers to what each tile produces for the city it belongs to. The three basic yields are food, production, and gold. I’ve turned on the yield icons in the screenshot below, so you can see what each tile yields:

Click/tap to enlarge: the details are important

The basic flat grassland tile yields two food (2F, represented by ears of corn). Hills on any tile adds one production (1P, represented by hammers), so a grassland hill tile yields two food and one production (2F + 1P). Woods on any tile adds one production, so a grassland woods tile yields two food and one production (2F + 1P), and a grassland woods hill tile yields two food and two production (2F + 2P).

The basic coast tile yields one food and one gold (1F + 1G, with gold represented by coins). An ocean tile yields just one food. Mountains yield nothing.

The presence of resources and natural wonders affects yields as well. Stone adds 1P to the tile yield, while fish add 1F. Wine adds 1F + 1G, olives add 1P + 1G, while horses add 1F + 1P. Marble adds one culture (1C) which is a yield we’ll discuss later; the Matterhorn also adds 1C to the yield of adjacent tiles.

This is a way for the game to quantify what each tile produces. Obviously this is an abstraction — in real life, not all farming is equal, and not all raw production is equal either — but in a game that operates on such a macro scale, this is an acceptable simplification.

You may notice that the popup on the stone says, in angry red, “Requires Mining”. This has to do with the technological tree, which I’ll talk about in a separate article.

Tile Improvements: Farms, Mines, Quarries, Plantations

The tiles we’ve seen so far are the Civ equivalent of greenfield or undeveloped land, but they do not remain so over the course of the game. Players can build tile improvements on tiles owned by their cities. These include (but are not restricted to):

  • farms
  • mines
  • quarries
  • plantations
  • pastures
  • camps
  • fishing boats
  • lumber mills
  • oil wells

Farms, mines and lumber mills can be built on any suitable tiles (flat grasslands/plains, hills, and woods respectively), while the others can only be built on a resource. Improving a resource tile gives your empire access to that resource.

In this picture here, I’ve built a quarry on each of the two stone tiles. This adds 1P to each of the two tiles:

The stone on the flat grassland was previously producing 2F + 1P; it is now producing 2F + 2P. The stone on the grassland hill is even more productive: its 2F + 2P have now increased to 2F + 3P.

Different tile improvements provide different bonuses. For example, the unimproved Olives tile provides 2F + 1P + 1G (and the angry red words tell us the tile “requires Irrigation”):

After building a plantation on the Olives tile, the tile now yields 2F + 1P + 3F:

(The eagle-eyed may notice that the tile’s appeal has fallen, from 5 to 4.)

In terms of modelling, it’s pretty clear what tile improvements model. Some areas are naturally richer in resources than others, which is where the base bonus to food or production or gold comes from. Imagine a region rich in, say, wild rice. That area provides you more food than an average grassland region without that wild rice. However, if you could domesticate that rice… that would provide you even more rice, even more food, per square metre.

Of course, tile improvements require technology. Before I discuss technology modelling in Civ VI in a future article, there’s something else that’s important to explain about the Civ VI model.

Modelling Time: The Turn

Full Civ VI games start in the year 4000 B.C., and end in the year 2050 A.D. These dates are arbitrary, of course — civilisation didn't begin in 4000 B.C., the empires featured in the game didn't (and don't) span that time frame. Some Civs in the game have histories that extend before 4000 B.C. (in particular: Sumer, China, India). Nonetheless, the game has to start somewhere, and it might as well be 4000 B.C.

To me, the more interesting question is: how do you approximate the passage of time in a game like Civilization?

Many simulation and grand strategy games have a panel with pause, play and fast forward buttons:

 Left: Project Highrise (top: paused; bottom: running). Right: Europa Universalis 4 (top: paused; middle: running at speed 4; bottom: running at speed 1)

Left: Project Highrise (top: paused; bottom: running).
Right: Europa Universalis 4 (top: paused; middle: running at speed 4; bottom: running at speed 1)

When the game starts, the player starts positioning their assets (whether roads, troops or anything else). The player can pause the game and spend some time crafting their next moves, then hit “play” and set the simulation in motion. During particularly slow stretches, the player can fast-forward and run the simulation at 2x to 5x the speed of regular play.

This is the most obvious solution in any game that is explicitly a model of some real-world analogue. Civ could have done the same, starting the game in the year 4000 B.C. and advancing the clock at a base rate of, say, ten years per minute, with the option to pause or fast-forward gameplay as it suits the player.

The problem with this game mechanic is that the speed of human technological, cultural and economic development has accelerated over time. Scientific and social developments have a multiplicative effect on human civilisation’s technological, cultural and economic output. The technological progress that humans made in the year 4000 B.C. is a fraction of the progress that we made in the year 2017. A pause-play-fast-forward game mechanic for modelling time would create a lethargic early game, with an overly dense late game that would test players’ reflexes and attention much more than their strategic abilities.

 A Civ VI game on Standard speed lasts 500 turns and ends on Jan 1, 2050 A.D. At the end of the game, each turn represents six months.

A Civ VI game on Standard speed lasts 500 turns and ends on Jan 1, 2050 A.D. At the end of the game, each turn represents six months.

Instead, the Civilization game series uses a turn-based rather than a real-time game mechanic. Players take turns to make their moves, and each turn represents a predefined timespan. In Civ, earlier turns represent a longer timespan, while later turns represent an increasingly shorter timespan. For example, Turn 1 lasts from 4000 B.C. to 3960 B.C., while Turn 499 represents January to June 2049 A.D. This way, the game remains engaging from start to finish, and the game model more accurately reflects the evolution of human civilisation with respect to time.

Population, working citizens and yield per turn

The combination of yield and turn-based time mechanics gives us the concept of yield per turn. At the beginning of every turn, the game calculates how much of each yield each tile produces, and adds up the totals per city.

Not all cities are the same size, though. A city with a low population cannot adequately work all the resources around it. As the city’s population increases, its citizens start working more and more tiles around the city. A city with a population of 1 receives the yield from the city tile and one other tile within its borders. A city with a population of 5 receives the yield from the city tile and five other tiles within its borders — and so on.

Logically, this would mean that you’d want your cities to be as big as possible, right? That is usually true, but bigger cities also require more food to feed, and that’s where the food yield per turn matters. Each citizen in a city consumes 2F per turn, so a size 2 city requires at least 4F per turn to maintain its population, and a size 5 city requires at least 10F per turn to maintain its population.

It’s hard to explain all of this abstractly, so let’s take a look at an example of this mechanic:

Let’s take a look at an example of this mechanic:

Click/tap to enlarge: the details are important

This is the city screen for the city of Ravenna. The number “2” next to the city’s name on the map tells us the city has a population of 2. (This doesn’t mean there are only two people in the city, obviously — the city population number is an abstraction, just like everything else in this model.)

The tile that the city sits on is always worked — that is, the city always receives the yield from the city tile (highlighted in green). In this case, that tile yields 2F + 1P. Additionally, each of Ravenna’s two citizens can work one tile within Ravenna’s city boundaries. In this case, the citizens have been assigned to work the two tiles highlighted in red. The northern red tile yields 2F + 1P + 1S (science, a yield we’ll discuss later in the series), while the southern red tile yields 2F + 1P + 1G.

This gives Ravenna a base tile yield of 6F + 3P + 1S + 1G. Tile yield isn’t the only way for cities to generate yield, but it is one of the most important yield mechanics in the game. (Buildings, city population and specialists are the other main ways to increase city yield, but I’ll talk about those mechanics another time.) After all the yield from tiles, buildings, city population and specialists is added up, various modifiers are then applied to the base yield to generate the city's actual yield per turn.

1 14 Ravenna City Screen Yield Bar.png

If you look at the bar above the “Ravenna” interface, you’ll see that each turn, Ravenna generates:

  • 2.7 culture (don’t worry about this for now)
  • 1.1 surplus food
  • 3.1 production
  • 2.1 science (don’t worry about this either)
  • 0 faith (don’t worry about this either)
  • 1 gold

The numbers aren’t all round numbers because there are various multipliers at play here (another topic for another post), but you can see that Ravenna’s gold yield per turn comes entirely from its olives tile (1G). The production base of 3.1P per turn comes from its three worked tiles (1P per turn each), plus a 5% multiplier because the citizens are happy (yet another game mechanic for another post). The city is building a granary, so the 3.1P per turn goes towards finishing that building, which requires a total of 65P to complete. Ravenna's already invested 36P in the granary, so at 3.1P per turn, it will take 9 more turns for Ravenna to finish the granary.

1.1 food per turn might seem surprisingly low, but the city screen is kind enough to break down how the food surplus is calculated, so we’ll take a look at that.

Food surplus per turn: modelling population growth and decline

Breaking up a map of terrain into tiles and assigning each tile a food value — that’s a pretty simple idea. Figuring out how food affects a city’s population is slightly more complicated. All things considered, Civ VI’s model is a very simplified one.

Take a look at the “Citizen Growth” panel on the left of the city screen. The city, with its three worked tiles of 2F each, generates 6 food per turn. The city has a population of 2, so the city consumes 2 x 2 = 4 food per turn. That leaves a surplus of 2 food per turn that contributes towards city growth.

Because the citizens are happy, there’s a 10% bonus applied to city growth, giving us 2.2 surplus food per turn. However, because there is barely enough housing in Ravenna (yet another mechanism to be discussed in a future post), the population growth rate is halved. That’s how we arrive at the final number of 1.1 surplus food per turn.

Under “Total Food Surplus”, there’s a “Growth” bar. Think of the growth bar as a food basket or a granary: the excess food gets added to the food basket every turn, and when the food basket is full, a new citizen is born and the city’s population increases by 1.

A city’s population can also drop if it generates less food than its citizens consume. In that situation, the food surplus becomes a food deficit. A food deficit reduces the amount of food in the city’s food basket, and when the food basket is empty, the city loses a citizen and its population drops by 1.

This model has the effect of scaling city yield with city population, but also produces a natural upper limit for each city based on how much food a city generates. If a city cannot feed itself, it cannot grow. Mature Civ cities reach an equilibrium where the total food surplus is at or close to 0, and stay at that size until the end of the game.

What Comes Next?

Civ VI is a complex game that is pretty challenging to learn. In this post, I’ve laid out some of the key game mechanics that we’ll need to understand in order to do a truly deep dive into Civ VI as a model of civilisation, but there’s a lot more to it. In the next post, I’ll explore two of the most fundamental game mechanics in Civ VI: the technological and civics trees. We’ll talk about how they work, and what kinds of assumptions they make about how progress happens.

Modelling Reality Through Games

In the (underrated) musical Chess by Björn Ulvaeus, Benny Andersson and Tim Rice, the cast explains how the game of Chess came to be:

Not much is known of early days of chess beyond a fairly vague report

That fifteen hundred years ago two princes fought

Tough brothers for a Hindu throne

The mother cried, for no one really likes their offspring fighting to the death

She begged to stop the slaughter with her every breath

But sure enough one brother died

Sad beyond belief, she told her winning son

“You have caused such grief, I can’t forgive this evil thing you’ve done!”

He tried to explain how things had really been

But he tried in vain

No words of his could mollify the queen

And so he asked the wisest men he knew

The way to lessen her distress

They told him he’d be pretty certain to impress

By using model soldiers on a checkered board

To show it was his brother’s fault —

They thus invented chess

This is a rather elaborate fiction, at least as far as I’m aware. There were no such duelling princes, and the idea that a mother would be consoled by a bunch of ivory pieces on a grid is laughable. What is true, and what is relevant to our discussion here, is that the game of chess did most likely originate in India, and it was likely used to some degree or another in the study of military strategy.

Chaturanga, the game that is considered to have evolved into chess, used six distinct types of pieces, as does modern chess: the Rajah (king), the Mantri (counsellor), Ratha (chariot), Gaja (elephant, Ashra (horse) and Padati (footsoldier). Their movement on the game board approximates their movement on the battlefield:

  • The Ratha moves like a rook in chess, in straight horizontal or vertical lines, mimicking a charging chariot.
 Rook icon created by LAFS from Noun Project (CC-BY).

Rook icon created by LAFS from Noun Project (CC-BY).

  • The Ashra moves like the modern chess knight, a slower heavy cavalry unit that is more adept at close quarters combat than the lighter chariot.
 Knight icon created by LAFS from Noun Project (CC-BY).

Knight icon created by LAFS from Noun Project (CC-BY).

  • The Gaja’s moves are less well-defined. The great fount of knowledge that is Wikipedia describes three variants:
 Elephant icon created by Icon Fair from Noun Project (CC-BY).

Elephant icon created by Icon Fair from Noun Project (CC-BY).

Conceptually, any of these movements would fit the role of a war elephant perfectly: slow movement that is adept at wreaking havoc up and down enemy lines. (The modern chess bishop, with diagonal movement limited only by obstructions in its path, is a Renaissance European invention.)

  • The Padati, the lowly footsoldier, can only move forward one step at a time, just like on the battlefield. They cannot retreat. I’m not sure why they capture diagonally — if there was a specific reason for it, it has long since been lost to the sands of time. To make up for the Padati’s handicapped movement, there are lots of them — eight, to be exact — and they start on the board in a horizontal line.
 Pawn icon created by LAFS from Noun Project (CC-BY).

Pawn icon created by LAFS from Noun Project (CC-BY).

What’s striking about this configuration is that this line of pawns mimics infantry movement in unexpected ways. Pawns are individually weak but in aggregate are used to form a strong defensive line. The middle pawns often advance to form a salient, claiming control of territory in the middle of the board, but can sometimes become isolated from the rest of the line. Two lines of pawns often face off in what is effectively a deadlock, unless a player can make a diagonal capture (mimicking flanking) or bring in one of the “heavy” units to bear on the line of pawns.

Of course, this comparison has its limits. Infantry does often form the frontline, but rarely does infantry enter the battlefield first. That role goes to reconnaissance units and light cavalry. Since chess is a perfect information game, there is no need for reconnaissance, but this limits its utility as a tool for exploring real-world military strategy. Additionally, in combat, long-range units engage before close-range units, but chess’s capture system models only close-range combat.

All models are inaccurate, some models are useful

Of course, none of this should reflect negatively on chess. Whatever its origins, it has long ceased to be a model for military strategy. What interests me is the abstraction of chess. In trying to create a high-level model of military strategy, many aspects of warfare had to be abstracted away. First of all, the terrain: a chess board does not model the advantages and disadvantages provided by different types of terrain. Secondly, the game does not account for asymmetry of manpower, matériel, or other force multipliers such as training or technology: both sides start with the same number and type of pieces. Thirdly, the game does not account for any asymmetry of information: you always know exactly where your opponent’s pieces are at any given time. This isolates the importance of battlefield tactics.

For a game, this is ideal, because this means that the differentiator between two players is the quality of their tactical and strategic play, and nothing else. As a model of battle, however, this limits the utility of chess.

Games as models of reality

With the rise and dominance of video games, the potential of games as models has gotten a lot more interesting. In particular, simulation, base-building and strategy games are often designed to be semi-realistic models of something that exists — or could exist — in the real world: SimTower is a model of elevator traffic, Cities: Skylines is a model of urban traffic, and SimPark (a sorely underrated game) is a model of the ecology of a park habitat. Some strategy games are models of hypothetical or counterfactual situations: Frostpunk is about surviving a volcanic winter in the year 1886, Surviving Mars is a model of a future colonisation of Mars, and Jurassic World Evolution is a model of a series of dinosaur zoos.

What’s interesting about these types of model-building is that they tend to be based on complex systems.

You may have heard of the Cynefin framework, which divides problem-solving situations into four types: simple, complicated, complex and chaotic. The chaotic condition doesn’t interest us here, as it’s typically not modellable. The best breakdown of the remaining three conditions I’ve seen comes from a paper on healthcare reform by Sholom Glouberman and Brenda Zimmerman:

 From Glouberman and Zimmerman (2002)

From Glouberman and Zimmerman (2002)

The Cynefin framework is designed to explain problem-solving circumstances or conditions, but that’s just the flip side of working on a system. A rocket is a complicated system and building one is a complicated problem. A child is a complex system and raising one is a complex probleem. A habitat’s ecology is a complex system and managing one is a complex problem. Urban traffic is a complex system and managing it is a complex problem. International diplomacy is a complex system and navigating it is a complex problem.

Games with the highest replay value are often built on complex systems, with many interrelated variables that are not strictly solvable through maths alone. This gives the player complex problems to solve that are never quite the same on each playthrough.

(An aside: if a computer is a logic machine built on maths and maths alone, it’s worth asking if any computer games are truly complex, as opposed to merely complicated: given an infinite amount of time and computing resources, couldn’t an optimal solution to any game be found? Well, yes — that is what speedrunners try to do. The most complex games have an element of randomness to them, but computers can’t really generate “true” randomness, which is also why random number generator (RNG) manipulation is even a thing. So, if you want to a total pedant: such computer games are, strictly speaking, systems that are so complicated they are, for all practical purposes, complex systems.)

Emergent patterns in complex systems: Cities: Skylines

A distinguishing feature of complex systems of any kind is that they will produce emergent patterns. Consider the pawn on a chessboard. The rules of pawn movement are simple: One square forward at a time. Two squares forward, if you wish, on any given pawn’s first move. Capture one square diagonally. And yet, within the game of chess, this simple movement gives rise to a whole range of theories and strategies revolving around pawn structure.

What some of the best games do is to create a model with similarly simple rules that create emergent patterns. Look at a city-simulation game like Cities: Skylines. You lay out roads, zone residential, commercial and industrial districts, place amenities such as schools and hospitals, and implement a public transport network. The game simulates up to one million individual citizens’ movements: people wake up, go to work, go to the shops, go home. At work, they take deliveries or make them. Students go to school and, in the mid-afternoon, hang out in town or go to their friends’ homes. Tourists go from airport to hotel to tourist attraction.

(click on any of the following images to enlarge)

A city I built: the main city in the north-east, with two separate “centres”, a large industrial zone in the west, and the tourist district in the south-east.

City rhythms emerge out of up to one million individual modelled movements. Here, citizen Ashleigh Dixon is going to Club de la Crème, and she’s on foot for this part of her journey.

At Ashleigh’s workplace, Aero Designs, a company van (with a donut on top) is leaving the industrial zone to deliver goods to Busy Corner Shop.

Outside the Busy Corner Shop, a public bus is running its route. This one is almost full.

This tourist has gotten hold of a bicycle, and he’s cycling to the Expo.

A tourist is walking to the Stadium.

Another tourist walking to the Stadium. There must be an event happening there.

There’s no way to see if there’s an event at the stadium, but you can see that it draws both residents and tourists.

A truck brings forestry products to the cargo train station near the industrial park for export…

… while another trucks moves forestry imports from the cargo train terminal to The Lumber Mill.

Imports can also travel the entire distance by truck. (If your city has coal or oil power plants but no coal or oil, they will have to be imported — and if the truck can’t get there in time, the plant stops running.)

Of course, exports can travel out of the city entirely by truck, too.

This commuter blimp is empty in the middle of the day…

… while this one, plying the route from the city to the tourist district, is full.

This tourist is leaving the city. Once he reaches the airport, he will despawn (I think).

Municipal facilities also generate their own traffic. Here, a fully-loaded garbage truck makes its way to the incineration plant.

Municipal services also employ people, adding to the realism of the simulation and the patterns that emerge from it.

By modelling individual movements, the game creates an emergent picture of traffic patterns in the city. People move en masse from residential to commercial and industrial districts, and then they go home en masse. Industrial districts generate traffic to commercial districts, as well as to and from other cities in the form of exports and imports. The sum of individual movements produces consistent patterns, and the joy of the game is to figure out how to make the adjustments that modify or constrain that emergent pattern.

In the case of Cities: Skylines, the key to managing your city’s traffic turns out to be isolating your industrial districts. Residential and commercial districts can mix, but industrial districts must be separate and have their own routes into and out of the city. (The fact that this is exactly how actual cities tend to be laid out is not a coincidence.)

Another Example: SimTower

An older and clunkier example of simple rules producing emergent patterns, perhaps, is SimTower. In SimTower, you’re tasked with building a tower that turns a profit and keeps all its tenants happy. Low rent makes people happy. Long elevator wait times make them unhappy. Having to travel far to get to a food or retail outlet makes them unhappy. People will use escalators where available, but never more than seven; people will use stairs where available, but never more than four. People will only change modes of transport once.

What these rules create is an emergent pattern of play that encourages players to keep their office tenants separate from the residential and hospitality tenants in order to manage traffic. Here’s an excerpt of a post from r/SimTower titled Optimal Tower Design:

Office workers should never be using regular elevators to get anywhere. Office worker population density is too high. They must be forced to take the stairs (disable elevator access to their floors!)

David Wolever reached a similar conclusion. Here’s a passing comment from his post detailing how he beat the game:

… You will need to make sure that the lazy sims working in the offices don’t use these elevators.

These two players have very different styles of play, but they converged on a principle of play that is not immediately suggested by the rules. Furthermore, this happens to be the solution that real towers employ to manage traffic: separating the modes of transport used by office tenants from other tenants.

 Optimal tower design: elevators do not run to offices.

Optimal tower design: elevators do not run to offices.

You might argue that no real-life tower would prevent office workers from using the elevators. This is obviously true, and points to limitations in even well-designed complex models: any model is an abstraction, and will abstract away important information to some degree or another. In this case, SimTower’s model assumes that all units of a floor are accessible from any other unit of the same floor. There is no way to create segregated office blocks or areas with a shared retail area. (Project Highrise, a more recent tower simulation game, allows this.) This leads to players artificially separating them by forcing office workers to use the stairs while residents get to use the elevators.

The educational value of games

If game models are flawed, what value do they provide? What can they really tell us about the thing they are modelling?

That’s what I want to look at next, with a thorough examination of Civilization VI and the gameplay that emerges from it.