THS-IPA: A Game-Theoretic Model of Transformation

This is my first attempt to articulate a coherent theoretical model of transformation, based on my dialogues with Prof. Agnis Stibe on Transforming Human Systems.

The Instigator-Population-Agents (IPA) model describes the dynamics of how an Instigator spreads behavior across a particular Population of Agents. While most commonly used for leaders attempting to transform a group of people, the model should also be applicable to individuals (via the society of mind interpretation), social animals, and even some computational systems.


Agents within a Population:

  • Interact over Time with Agents and the Environment through Games
  • Use tangible Resources and intangible Status to play and win Games
  • Seek to gain (but often lose) absolute Resources and relative Status by playing (or declining) Games
  • Have a diversity of Values (which determine which Games they play) and Capabilities (which affect which Games they can win)
  • Act with conflicting Intention but imperfect Information, complicated by Values that vary with Time and Environment

We can define Flourishing as the aggregate Resources and Capabilities of all Agents within a Population. Thus:

  • Pro-social Games increase Flourishing
  • Zero-sum Games do not affect net Flourishing
  • Anti-social Games decrease Flourishing (usually by benefitting specific Agents at the expense of the Population)

Meta Games

Importantly, the Instigator is also considered an Agent. This means that any transformational intervention (e.g., encouraging the washing of hands during a pandemic) involves at least two Games:

  1. The base Game of each Agent (actually washing their hands)
  2. The meta Game of the Instigator (getting everyone to wash their hands)

This leads, in general, to a game-theoretic conflict between the Agent and the Instigator. Even if the base Game is truly pro-social, the Instigator is almost certain to increase their relative Status by getting everyone to play it. This leads to several complications:

  1. Anti-social Agents who would lose the most Status are motivated to sabotage the base Game to avoid losing the meta Game.
  2. Anti-social Instigators who would gain the most Status are motivated to disguise anti-social base Games as pro-social.
  3. Pro-social Agents must find signals that enable them to overcome both (1) and (2).

Sometimes, this distinction isn’t important. For example, if the Instigator is already has maximal Status and alignment with a homogenous Population (e.g, the founder of business), then the likelihood of conflict between the base Game and meta Game is low. However, because humans are Machiavellian status-seeking primates, Agents must assume that any Game worth winning is worth cheating for, and develop strategies to compensate.

Compensating Strategies

This is why social proof is so powerful. If a high-Status individual (or the community as a whole) adopts a particular Game, the likelihood of it being injurious to a specific member of the community is low.

Another powerful signal is renunciation, where the Instigator publicly gives up access to the Resources (and perhaps even Status) they would otherwise enjoy from winning the meta Game. We can see this historically in the way medieval priests forswore family and riches, and in modern times where CEOs such as Steve Jobs and Lee Iacocca accepted one-dollar salaries.


2 Comments on “THS-IPA: A Game-Theoretic Model of Transformation”

  1. […] THS-IPA: A Game-Theoretic Model of Transformation → […]

  2. […] is my first draft of such a vision, building on my earlier THS-IPA: A Game-Theoretic Model of Transformation. I welcome your […]

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