This post will be a little bit more “roaming through knowledge” than the usual.
Actually, it is part of a series, first published in May 2009.
But, following the dictum of somebody else, I will make things as simple as possible, but not simpler.
What is the point? Talking about ways of representing and forecasting the expected decisions of groups and individuals, and some projects that try to build a “model” of what we are and could be- be it our DNA or our brain.
And, while doing this, recalling some useful concepts that you can apply in whatever you do in your business and personal life- including when you are on the receiving end of the results of a model.
As usual- theory is converted into (hopefully) plain English, and the examples are from real life and experience in business, politics, technology- and their impact on personal and business life.
PREVIOUSLY
GMN2009: REALITY
When you build a model of reality, you try to reduce complexity.
Reducing complexity means making choices- and reducing the risk of something unexpected affecting the results of your model.
Actually, it means also reducing the number of parameters- and, therefore, making any evolution in your world more predictable.
But reality is not necessarily limited by your definition: and managing the reality within a model requires more that planning beforehand for what you know, in terms of activities or risks.
You have also to identify what is the “normal” way in which your model will react to unexpected changes in the “reality” surrounding your model.
GMN2009: GAMES
Before the real article… an exercise for your mind.
What is a game?
Do not cheat 
by visiting sites or wikipedia or going to pay a long overdue visit to the nearest library 
You will get something that includes those sources later in this section.
Meanwhile, think about what defines a game, its rules, its environment, and, most important of all, its relevance/purpose.
STOP READING NOW.
And to ensure that…
And now, back to games.
You want your model to work in reality, and therefore you have to assume that others have their own models.
It is a game. Like playing chess. Or the usual “prisoner’s dilemma”.
From models, we will move to the interaction between models- and between different decision paths within a model.
A down-to-earth introduction to the game theory.
But, I am sorry for you, this section will draw heavily on concepts that consumed tons of ink.
And you are lucky: you can read just these few pages, or jump around the web and read linked documents, books, articles, etc- beyond and above Wikipedia.
A game is game
Did you think what is a game?
Fine. Now, forget about thinking. Became a cultural anthropologist, and observe games.
Including the word games that you do.
As Wittgenstein wrote:
“66. Consider for example the proceedings that we call “games”. I mean board-games, card-games, ball-games, Olympic games, and so on. What is common to them all? — Don’t say: “There must be something common, or they would not be called ‘games’ “-but look and see whether there is anything common to all. — For if you look at them you will not see something that is common to all, but similarities, relationships, and a whole series of them at that. To repeat: don’t think, but look! “
So, let’s see first simple games with words through pictures:
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Escher
Two word games- the latter being, in my humble opinion, better.
Magritte’s: the denial of what you yourself declare.
Escher’s: “monniken werk”- in Dutch, “monk’s job” is something that is akin to the famous suggestion of paying somebody to dig holes, and then pay them again to fill the holes 
Again Wittgenstein:
“67. I can think of no better expression to characterize these similarities than “family resemblances”; for the various resemblances between members of a family: build, features, colour of eyes, gait, temperament, etc. etc. overlap and cries-cross in the same way.-And I shall say: ‘games’ form a family.”
And why these references and quotes?
Because picture and words from somebody else will probably be more interesting and memorable that discussing for pages over pages about the definition of a game (and yes, providing cocktail party trivia is always a good way to fix a concept in the mind of the readers).
Let’s just say: within this series of articles, a game is activity or set of activities that you define to achieve some purposes and involves yourself and others within the game.
Their participation should not necessarily be transparent- and the others do not necessarily be involved in sharing the results of the game, or know the rules.
As you can see, neither I nor any of the examples discuss the concept of “form”, “structure”, “rules”.
Those are part of the framework that you defined with the stakeholders for your activity.
Yes- in my view, any structured activity is a game. Because it is focused on the research of an outcome.
And in order to achieve your outcome, you provide and consume resources- and need to budget.
Be it time, money, number of players, objectives: anything is negotiable and can be structured (more about this in GMN2009: PLAYING).
And before moving the practicalities, let’s take another small detour to the library.
What is the game theory? Probably, most people heard of it from the movie about John Nash, “A Beautiful mind”.
If you want a formal introduction… you can refer to an historical classic (1954), available for free on the RAND Corp. website (free Acrobat)
A more recent (2006) overview not just of the recognized founder of the game theory, John Nash, but also others, is available at The National Academies Press (incidentally: the title is “A Beautiful Math”).
And what if you want to be able to talk about the game theory at parties, but without spending more than, say, 10 minutes? Go to Wikipedia.
But if you are really serious, after all the appetizers… following the new approach of US universities, Yale posted online a full course on the game theory Game Theory with Professor Ben Polak.
In writing, audio, and video (yes, including the exams and the full 24 lessons across one semester about 2GB of material)
The shortest definition? From “A Beautiful Math”, page 2:
“Game theory originated in efforts to understand parlor games like poker and chess, and was first fully formulated as a mathematical tool for describing economic behavior.
But, in principle, game theory encompasses any situation involving strategic interaction- from playing tenning to waging war.
Games theory provides the mathematical means of computing the payoffs to be expected from various possible choices of strategies.”
As you can see, the mathematical theory covers discussing the games and the actual interaction between the parties involved in the game.
The next section, GMN2009: PLAYING, will discuss in details the “playing” part- when your game becomes reality.
But my approach to games is linked to reality and activities that you define and execute, not just activities that you receive.
Therefore, a knowledge of the game theory is useful also in defining “the game” and its components: ways, means, rules, participants, and so on. And, of course, its desired outcomes.
The good news is: the quotes that you read here, and thinking about the pictures: is all that you need for the time being.
You do not need to read any of the linked material right now- not even the Wikipedia article.
So, in the spirit of this blog, let’s start with first-hand examples in game design.
Being born in 1965, implies that I grew up with the first generation of the videogame machines- have a look at a movies from late 1970s, and you will see those clunky boxes with tiny bricks and a paddle- nothing like the machines available today.
But in early 1980s “microcomputers” started spreading beyond the technically-minded.
Actually, your mobile phone has games that are more advanced than most games then available for the home users.
At the time, most games inherited the gaming logic from either books or board games: a sequential model (see GMN2009: MODELS).
A game was considered as a set of steps to get through, with some specific rules on what to do in each step.
If you failed, you knew that, in order to move forward toward the goal, at a certain point you would have to do something that you failed before.
Eventually, “saving” the game was allowed. To restart not from the beginning, but from the point when you last “saved” your game.
Frankly, it was boring- unless you were really an addict.
But there were some interesting, small innovations (see GMN2009: CHANGE).
Some games included items that moved according to separate rules- not really intelligent, but able to create a combination of “indipendent” behaviors that actually wrecked your carefully planned (see GMN2009: PLANNING) path toward achieving the objectives set by the game designers.
Therefore, you had to start constantly observe and monitor (see GMN2009: PROGRESS), so that you could know what to expect.
But all your monitoring would help you only to avoid what you knew.
So, you had to build up the reflexes needed to be able to manage the unexpected (see GMN2009: RISK).
And all these games (as most of the current games) were actually not so exciting: play it once, and you probably will know all the options, as the game did not learn.
They did not evolve.
Hence, after some toying with decision theory, I started studying about expert systems, as a way to move forward in my ideas of building models of knowledge in specific environments or what I would call now “knowledge domains”.
In 1984, during the first year at the university, I prepare the “rules” for a game of ecology, based on building a behavioral profile for each item, and then set the targets for the game politically- the desired balance in the environment.
Slightly manipulative? No. Completely.
As most training and games are.
They represent the reality designed by the game creators (see GMN2009: REALITY).
I checked with a professor in simulation, but he said that our studies were focused on discrete simulation, while I wanted to create continuous simulation.
He told me that I should the Douglas Hofstadter book “Godel, Escher, Bach” (sorry- no umlaut on my keyboard).
From that attempt, derived by digging into an artificial language called “PROLOG”.
The idea? Still the same- each item in the game was to have a “life”, with rules.
So, you have a game- the lifecycle of each object, and its profile.
And another game- the interaction between the objects.
And another game- the interaction between the player and the objects, all interacting with each other.
Did I complete the game- well, bits and pieces and concepts.
Then, I was called for a completely different game- in the Army (I had been waiting from the year before).
And, few years later, I used the concepts that I had developed for more serious activities, in consulting for decision support systems.
As you can see from this small example, something as simple and as controlled as my proposed ecology game was eventually to be the seed to develop other activities.
But defining any non-trivial game, be it a simple project, or the joining of different components, generates a key concept: a realistic game needs to introduce the concept of interaction and side-effect.
The example from my attempts at building in early 1980s something more “intelligent” shows that rules are but part of the work involved in defining the game.
Between people, if you are inside a game, you cannot make a choice. You have to play the game.
But knowing the rules will not help you- unless you also understand the profile of each other participant in the game whose activities could affect you (directly or through others).
Their motives- their own individual games.
And how each game can interact with the others.
More about this management of the interaction will be discussed in the next section, GMN2009: PLAYING.
But it is important to move one step back- and focus on the design of games.
Personally, when I have to design, say, a negotiation, I try to design a profile for each involved party.
And now, you understand my joke (the picture shown above): “Remember before using your brain that information seeds decision”.
I lost count of how many times I was involved in negotiations for something not really critical (a software or consulting or service project), and felt as if people were so focused on micro-managing, that forgot that all their strategies were worthless.
The had converted a strategy into an operational plan, and skipped the phase when you collect information.
Moreover: the “fog of war” will always be part of any activity- but it should always be factored in, as discussed in previous sections, by balancing between the cost of doing something without knowledge, and the cost (including the postponement in time) of procuring the knowledge required to reduce the uncertainty.
Anyway, be it a new activity, like a startup, or a project, I do not believe that uncertainty can be reduced to zero.
Whenever I saw an activity where everything went absolutely as planned- I was puzzled. Because it meant that, probably, the activity was living in a vacuum, subject to no interaction with reality- and that its results were probably useless.
If you are designing your own games based on identifying first and foremost of the stakeholders’ profiles and motivation that produced the activity, then you can also better control the uncertainty.
As you will have framework of reference, a benchmark for your choices.
Also, knowing the motivation of your “initiators” allows you to focus your resources on controlling uncertainty where it matters.
I saw activity and project managers living in a constant state of almost hypnotic confusion and stress.
Stress is useful in managing and evolving games and rules via interaction.
Controlled stress.
But do not forget that stress is also… stressful, and generates a feed-back also on your own possibility to manage.
If you generate stress, and manage by stress- well, kicking around people is not the best way to keep them motivated.
To summarize, a short checklist from experience on game definition
First, understand why.
Second, understand who are you designing the game for- your real audience.
Third, profile your audience and any other relevant party involved.
Fourth, disclose via brainstorming as much as you need from your profiling to your audience to help them prepare for the game and to help the game achieve its purposes.
Fifth, create the description, the rules, and the communication about the game, and identify guidelines for “the players” (your audience), as you want them to be successful.
Sixth, if it is a negotiation or an ongoing activity (e.g. change or organizational management)… see the next section.
The fourth point could be puzzling at first: but how often you have stakeholders that are not the real stakeholders?
Chinese has two nice concepts, “mianzi” and “guanxi” (go on Wikipedia- I will come back to this in the next section).
What is really important to consider is also if you will be yourself part of the game- or if your task will be completed once the game design has been completed.
If you create a game for somebody else (including a videogame), then you have to consider if and how to keep yourself outside the picture.
Nothing is worse that a change facilitator that tries to actually decide the direction of the change.
If you build a game: you are a supplier of a product (the game and all the ancillary activities).
I could write tens of stories of consultants that thought that they knew better than their own customers what would be needed for them- and forgot that the supplier-customer relationship is a game in itself.
When designing a game for somebody else, do not forget that you will receive only the information that the stakeholders assume that you will need to design the game, not those required to manage the interactions while playing the game.
If you have some time, before moving to the next section, go online and play one of those MMORPG games (Massively Multiplayer On-line Role Playing Games).
Why? Because you will then learn how, given a general framework with some rules, each player is an independent rules-setter, with his/her own strategy and purposes- and not necessarily following the rules the way that you expected.
Frankly- I would suggest some strategy-based gaming with longer-term objectives (I liked the old Warcraft, a little bit less Starcraft)- the twist and changes give you a more realistic way to react to change than the old board games, limited by the need to have you move all the pieces around.
The reason? Humans have always a surprise in stock- and the social dynamics that you can generate while creating a team (also with the computer, like in the old Warcraft) are quite interesting.
Finally- if you fail in the game, nothing is lost.
But you learn something about your own weaknesses in stress management and decisions making, that you can then apply in games that matter more to you and your activities.
And design your own games accordingly.
NEXT
GMN2009: PLAYING
Moving from designing the game to using the game implies adding a completely different set of skills.
You will need to learn how to manage the evolution of the dynamics between the players- be it a simple game, a real negotiation, the management of a major organizational change, a merger, or a political campaign.
Playing games implies being able to constantly feed back into your game the results of what you are doing.
From designing the game, we will move to evolution- something that is not necessarily following your strategy- but that you have to cope with.
Tags: artificial, benchmark, change, game, gmn2009, hofstadter, intelligence, management, methodology, model, nash, negotiation, organization, prolog, real, reality, stakeholder, theory