Mike’s GDC Survival Guide

Posted March 8, 2018 by Mike Sellers
Categories: industry

Tags: ,

Last year I wrote a “survival guide” for my students going to the Game Developer’s Conference for the first time. I’ve been going to GDC for about 22 years, and this is based on what I’ve learned.

This year I added to the survival guide and posted it on Facebook, where it was extremely popular. It’s on Google Docs, so I thought I’d post a link to it here too. Feel free to use this and pass it along (without changes and with attribution, please).

The doc is split into these sections:

  • Before you go
  • Things to bring
  • Basic survival in San Francisco
  • Helpful places to know
  • At the conference
  • Be social and professional

If you have bits of GDC wisdom you’d like me to include, let me know!

I hope to see you at the show!


Advanced Game Design: A Systems Approach – published!

Posted January 29, 2018 by Mike Sellers
Categories: education, game design

I’ve been encouraging (requiring) my students to post regularly on their accomplishments, difficulties they’ve gotten through, and things they’ve learned on their development teams. Naturally enough, I should be doing the same.

So here’s my first post in awhile, which also acts as a partial explanation for the long absence: last month my new textbook, Game Design: A Systems Approach, was published by Pearson Education!

This book is intended to be a guide for anyone interested in game design, especially at the university level. I wanted to dig deeper into the foundations of game design (in terms of game design theory, not history), but without neglecting the day-to-day practical elements, so the book is divided into three sections: Foundations, Principles, and Practice.

As discussed in detail in the first section, the root of this is really systems thinking and how it informs (and is informed by) game design. This is something I believe will lead us to be able to design better games, and puts the book on a more secure foundation, rather than being a bunch of ad hoc practices (which, admittedly, still describes a lot of game design). This section also covers the “what is a game?” question in a new way, given the basis of systems thinking. This framework also allows an approach to interactivity, engagement, and even the thorny question of “fun” in what I think are new and fruitful ways.

The second section gets to the heart of game design, again using the systems thinking perspective. I’ve found it useful to separate the whole experience, the systemic loops supporting it, and the parts and their behaviors that create these loops into three separate areas — and to likewise separate game designers into storytellers, inventors, and toymakers based on their individual inclination. We all seem to have a “home” that we start from — the “nouns and verbs,” the dynamic system, or the eventual player experience. Recognizing this and building the design process around it heads off a lot of arguments and helps designers with different talents and focus areas to work together.

The final section has two chapters on game balance (methods and practice), followed by a chapter devoted to what it means to work effectively as part of a diverse game development team, and a final about all that goes into making a game idea real — from pitching to prototyping to the phases of production.

My hope in writing this is that it serves two complementary purposes: that it provides real, tested, practical game design guidance, and that it does so within a useful, systemic framework. My belief is that “systemic games” win out over “content games” in terms of engagement and long-term replayability, a subject I’ll return to here in later posts.

This has been a long project – about 18 months of serious writing, plus a good six months of deep research before that. I’ve been poking at systems design and the confluence of systems thinking and game design for some time, starting many years ago with engaging conversations with Charles Cameron, reading Christopher Alexander, and leading to some wonderful group-work that resulted in a 2014 report from Project Horseshoe, followed by a lot more in-depth reading (Meadows, Capra, Luhmann, etc.). All of that, plus a great deal more than I’m leaving out, led to me writing this book. I hope that others find it useful in digging deeper into game design.

AI, Opinions, and Politics: Polarization and Distance as the Result of the Connected Age

Posted June 3, 2017 by Mike Sellers
Categories: AI, politics

Tags: , ,

On June 2, 2017, CNN Correspondent Bill Weir was interviewed about the journey he’s taken around the US, interviewing people for the show “States of Change.” He was asked by the host, Kate Bolduan, about what surprised him in what he heard from people.

Weir responded, “What I was surprised about is how distant people are in the most-connected age in human history.” This remark struck me for its obvious truth, and because it reminded me of research I had done years earlier. The simulation we created was difficult to explain at the time; I wonder if now it resonates more clearly.

In 2005, I was leading a team working on artificial intelligence in association with the Defense Advanced Research Projects Agency (DARPA) for creating “social AIs.” As part of this, we became interested in how opinions passed between individuals in a population, and what this meant for the population overall. This topic underlies all sorts of social interaction including reputation and political beliefs.

To test out some of our ideas, we set up a fairly simple simulation of “agents,” each represented by a little dots that had two opinions of abstract subjects. We represented these with colors – green and red. An agent that liked green and not red would show up as bright green. One who liked red but not green would show up bright red. An agent who liked both would show up yellow (the combination of the two colors), and one that liked neither would show up as black (the absence of both colors).

start condition 1

Starting condition for 200 agents (and two “kings”) with random placement and opinions.

These little dots start off randomly distributed around a space with random opinions of both green and red. Each agent would move about randomly, except that they liked to be near other agents with similar opinions as theirs. Each agent would tend to congregate near those with similar opinions, and move away from those with differing opinions.


Each agent also had a number of “associations” – essentially, which agents were its friends that it listened to, as each one broadcast its opinion (“I like red a lot and green a little!”) at regular intervals. Friend-agents might have different opinions, and on hearing a friend’s opinion, an agent might change its own views. The probability of an agent changing its view depended on its “Breadth,” that is, it’s openness to new ideas (modeled after the Five Factor Model of personality) and the strength of its association with another agent. The more broad-minded the agent and the stronger its association with another, the more likely it would be to adjust its opinion based on what one of its associates broadcast to it.

We also introduced two “kings,” agents with firm opinions of “pro-red” and “pro-green” that exercised an outsized influence on the other agents. Think of these as “thought leaders,” whether in the media, politics, fashion, etc. The dots (up to 200 agents plus the two “kings”) start in random positions with the agents having random opinion values.

simulation condition 2

Midway through a simulation: different agents are starting to coalesce in their opinions and locations.

In the simulation shown here, each agent has an association with about 10% of the others, and a 10% Breadth. As the simulation progresses, the two kings repel each other and move as far away from each other as they can. The other agents continue to influence each other, gradually finding their own place and adjusting their opinions based on what those around them say.

end condition with bridge

Late in the simulation: Red and Green factions have formed, in this case with a centrist bridge between them.



Eventually, the simulation settles into one of a few common patterns. Here, Red and Green factions are still both strong, but there’s also a “bridge” between them of agents who have more moderate opinions. This is the result we get when each agent only listens to a few others.





end condition factions 1

Two highly separated factions. Each is its own echo-chamber, with agents reinforcing each others’ opinions.

On the other hand, if we change the parameters of the simulation, we can get very different results. In particular, by making the agents far more connected – 100% associations, so everyone hears everyone’s opinions – the late-stage simulation looks markedly different as you can see here.


In cases like this, two distinct factions have emerged, all-red and all-green, with little or no common bridge between them. This didn’t happen every time, but it is common once you have a highly connected population.

end condition factions 2

Two distinct factions with a weak bridge between them.

Some variations include a weak bridge between the two main factions, and sometimes a variation of a “leaderless” third faction that is strong (or weak) in both, but not accepted by either faction.



end condition factions 3

Another variation with a highly connected population: two main factions with two “leaderless” factions (red+green and neither red or green)





The critical variable here is connectedness – how many of the agents are connected to and listening to others. It seems counter-intuitive, but in the first case above, when agents have only a few others that they listen to – a local “social horizon” – the eventual result is less polarized: there’s more variance of opinion, less echo-chamber effect, and more centrist agents bridging between different factions.

Conversely, when agents become more connected, they also become more polarized, more like those around them. This means that all or nearly all the agents retreat into an us-versus-them echo chamber where factions become deeply entrenched, self-reinforcing, and without contact with others who disagree even mildly. This reduces communication between factions, with all the attendant problems we see today.

What struck me in listening to Bill Weir on CNN was how pervasive and obvious this situation is to us now, and how unknown it was just twelve years ago. Today we all know about echo chambers and “fake news” and the entirely disparate narratives that different political factions hear. We have an idea that this is weakening our society, but maybe we don’t quite all see that yet. In 2005, these results were seen by people at DARPA and at various AI conferences, but induced more head-scratching than anything else: people didn’t understand the population dynamics at play, and they couldn’t see how a population could become so polarized, especially if they were also so deeply connected.

Today, I think we’re living out what this simulation shows. Maybe it’ll be more understandable now?


The societal effects of cognitive technologies

Posted September 19, 2016 by Mike Sellers
Categories: AI, economics

In Malaysia, Uber is easily available. It’s inexpensive, safe, and a great experience all around. Unfortunately, taxi drivers there don’t take kindly to Uber drivers — a few yelled at one of the cars I was in while visiting last week, and one slammed his fist into the window by my head as we drove past. You might say their rage at this technology-driven change is palpable.
Okay, now magnify the situation many times over: what happens, societally, when a significant portion of our existing jobs just evaporate in the space of a few years — enough to take unemployment in the US from 5% to 12% in less than a decade? Keep in mind the unemployment rate peaked at 10% in 2009 after the global financial crisis, and could easily be right back up there in just a few years. According to a recent Forrester Report, this is what we’re facing due to increased automation and “cognitive technologies.”
In fact it’s sort of worse than just going from 5% to 12% unemployment. According to Forrester’s projections, 9% of jobs in 2025 will be new ones enabled by automation, which is great — but 16% of existing jobs will have vanished forever. It’s not difficult to imagine that this might create a lot of economic and social dislocation along the way. All the displaced taxi drivers, truck drivers, customer service personnel, store clerks, fast food servers, and others will have to do something to keep themselves and their families going, and telling them to go back to their local community college is really not going to cut it. As Andy Stern, former president of the Service Employees International Union put it, that advice is “probably five to ten years too late.” He goes on to say that as a society “we don’t really have a plan and we don’t appreciate how quickly the future is arriving.”
There is a saying often attributed to Winston Churchill that “Americans can be counted on to do the right thing after they have tried everything else.” It seems that right now we’re still madly trying “everything else.” Jobs already lost or that will be lost to automation and globalization are not going to be magically brought back by “building a wall” on our border with Mexico, nor by instituting draconian protectionist measures or anything other backward-looking solution. We have to look forward to try to figure out what a radically different future actually means for us as a society. Until we decide to do so — until we finally decide to knuckle down and do the right thing — it’s going to be a difficult, bumpy time for a whole lot of folks. What’s coming at us now is going to make 2009, and maybe even the 1930s, look easy. The question, as posed by Stern, is “what level of pain do people have to experience and what level of social unrest has to be created before the government acts?”

“What should game developers learn from Blizzard failing at Titan?”

Posted April 22, 2016 by Mike Sellers
Categories: game development, industry, MMOG, Uncategorized

Over on Quora I was asked to answer this question. Here’s what I wrote:

A few clear lessons come to mind:

  1. Most games fail. Having a team that is smart, passionate, talented, deeply experienced, and insanely well-funded doesn’t change the fact that your game is most likely to fail.

    Let that sink in for a moment.

    Not even having had an enormous success one time means you will be successful the next time. Hard as it is to say, if you’re lucky this happens before the game is released (or even announced!). The long droughts between successful games is part of the landscape of the games industry, and something almost everyone has to internalize.

  2. Failure is not permanent. The story of game development and the games industry is nothing if not one of re-invention. Developers, properties, technologies, and companies all re-create themselves every few years. You try something new, you fail, you try again. Just as success is not a given, neither is failure. You fail, you sit, you cry, you mourn, and then you get up and try the next thing. That’s been my experience in more than two decades in the games industry.

  3. Know who you are. While re-invention is pervasive, it’s also true that success breeds inertia: the longer your company is successful at doing what it does, the harder it is to change that course. Is your company about ground-breaking innovation, or about tweaking known formulas? Both can work. But culture is real. Cultural inertia is real.

    Here’s a story I don’t often tell too publicly: in 2002, I interviewed at Blizzard for the lead design position on this new game they had going, World of Warcraft. I had recently been the lead designer on three MMOs (Meridian 59, SimCity Online, and Ultima Online 2 — one out of three of which were released), along with leading the design on The Sims 2. I had a really terrific day talking with the team at Blizzard. But every time I said something like,”oh that’s cool, and you could really take this in a new direction,” the response was along the lines of, “well… we’re really not trying to reach too far with new things on this project.”

    At the end of the day I sat in a conference room while the managers conferred. While I did, it became really clear to me that this was a great team and a great company — and definitely not the job for me. I’ve spent my career trying (and very often failing) to do things that were really new, and that’s not what they were trying to do. So, when they came back in the room (I’m abashed to say I don’t recall now who it was I talking with), they very graciously said, “we like you, the team likes you, you have a great resume… but we just don’t think you’re the guy for the job.”

    I feel incredibly fortunate to have been able to interview for that position, and even more fortunate to have been able to respond, in that moment, “You’re right. This is a great project and team, and I’m not the guy to lead it. But I think I know who is.” I recommended Tom Chilton, a terrific designer who was on the team I had just left, and someone who was a classic fantasy MMO designer in his bones. Not too long after that he took the job, and is still at Blizzard doing great work.

    The point of all this is that at that time, Blizzard knew who they were and what they wanted. They had an established culture and they played into their strengths in phenomenal ways.

    But that strength also made it more difficult for them to in fact do something new, to make whatever it was that Titan would have become. I mourn with them a bit for what might have been, but I also celebrate their re-invention via Overwatch.


Is there another way?

Posted April 19, 2016 by Mike Sellers
Categories: corporate, game development, industry, practice

Game dev folks, I’d like your thoughts on this one: Michael Martinez, CEO of JuiceBox Games, wrote a smart and heart-felt mini post-mortem of his company, which is shutting down. In it he details the difficulties of running an effective game development business in today’s market. 

I don’t know Martinez, but I agree with most of what he says 100%. And of course I have immense empathy for him and his team, and the difficult decisions he’s had to make.

That said, I’m left with the nagging feeling that he (and many other smart people) have bought into the equation of “game dev success” that requires many millions of dollars of investment. JuiceBox had a $2.54M seed round, the kind of money which then requires hit games to sustain the business. This view is hardly new; it’s how people have been setting up businesses for a long time (and how I’ve set up some of mine in the past). However, it also leads to the kind of tunnel vision that makes the conclusion that “games are a hit-driven business,” inevitable. It’s the classic (if often self-defeating) “go big or go home” mentality that shoves aside all other possibilities. The thing is, I don’t think that conclusion is actually all that inevitable: we can do this differently, with less risk and more success.

Read the rest of this post »


Chefs, creativity, diversity, and our old friend risk

Posted September 13, 2015 by Mike Sellers
Categories: Uncategorized

I’m on the outbound leg of a trip from the US to Sweden for the Sweden Game Conference. On the plane from Chicago to Frankfurt I watched the movie “Chef” again. It’s a small but worthwhile movie directed by and starring Jon Favreau. He plays an accomplished chef who is sick and tired of having to cook the same old menu over and over again. He’s lorded over by his money-guy who just wants butts-in-seats and for the chef to give people the mainstream fare they want. This results in a disastrous review, and the chef eventually flips out and leaves. He then goes on a journey of self (and family) discovery, and ends up  opening a small food truck that gathers a big online following.

So you can see, this is really a post-Iron Man/Avengers movie about making movies. It suits the making of games equally well — with the exception of the “all’s well that ends well” ending that most movie and game creators don’t experience.

Which brings me to this article from the Guardian. I fully agree that our range of “acceptable” game genres has narrowed to the point that our diversity issues go far, far beyond “we don’t have enough women represented in games.”  The result of this is that I often don’t find much that’s really interesting to play — and those games that do catch my imagination (and dollars) are often the smaller indie efforts – FTL, Banished, Sunless Sea, Prune, and most recently Kings Quest, which at least feels like an indie effort (which is an accomplishment for the developers in today’s environment).

Like many others, I believe that we are far too insular in many parts of game development, and that increasing our underheard voices (including but not only women) has been a distressing serial failure. As the Guardian article points out though, our lack of diversity extends far beyond how women are represented in games or how many women we have in leadership positions in game development. This narrowing extends well into the kinds of games that get made — and thus the kinds of games that get played. The developers often serve a narrow audience, which further narrows the demographic pool of people who are interested in game development, which sets off a vicious cycle.

In the middle of this though is the problem that game developers, like anyone else, want to be paid for their work. Absent a wealthy and disinterested patron (please let me know if you find one of those), being paid requires running a business — and games are most definitely a business. Businesses are necessarily risk averse; the chances of complete failure are just too high otherwise. Creativity and diversity are inherently risky. Therefore most successful game companies will avoid creativity and diversity as much as possible, and in doing so end up contributing to the (at best) reluctant relationship with diversity, and the narrowing palette of game genres deemed worthy of consideration.

TL;DR: We want to be creative and diverse, but all the necessities of making games professionally are set against this.

What to do about this? I don’t know. I don’t have any answers.

I have a few hopes and hypotheses: for example that as we increase the diversity in the pool of developers, we’ll find new ways to make games without increasing our risk — and that maybe, just maybe, some of the wildly successful game companies we see today will look past their IPO or current stock price (I can dream) and actually invest a certain amount of their healthy profits on on-going,long-term R&D. You know, the kinds of things that fail a lot, but eventually give us iPhones, self-driving cars, or the ability to choose from dozens of movies on a trans-Atlantic flight — the very kinds of investment most game companies have little interest in making.