Adventures in Game Theory, Part Three

To those fresh to this sequence of postings, let me give you a little context. Two posts ago, I implied that some kind of wildly significant insight about how organizations and societies worked could be derived from looking at simple playground games like Rock Paper Scissors. Over the course of the last two posts, I’ve been building up the case for that statement. Now comes the next thrilling, life-changing installment—this time with some simulation results!

Before I can fully explain, though, first I have to give you a little more background.  Last week I had the good fortune to speak at the ASTD conference in Orlando, Florida, the world’s largest training and development business event. The topic of the session was the use of Tokenomics as a tool for organizational culture change. I delivered the talk with my good friend Cindy Ventrice, from MakeTheirDay.com, and to support the session we captured a large amount of material on the subject, which those interested can find on our collaboration website, techneq.com. The session went wonderfully and generated plenty of interest. However, what I’m most keen to talk about here doesn’t relate to that talk, exactly, but to the unexpected consequences of it.

In order demonstrate to the audience what the Tokenomics approach was capable of, I put together a short computer simulation based on Scissors Dilemma Party, a game which the readers of the last two posts will have already heard of. The simulation was designed to show how autonomous software agents, given nothing but a simple memory model and some behavioral rules based on token acquisition, would automatically aggregate into social groups defined by shared values.

To make the model more intuitively approachable for a conference audience, I chose to have the agents move around in a virtual environment rather like people in a workplace, interacting when they met. As well as making the simulation more visually appealing, it demonstrated how the agents’ behavior evolved over time as they learned more about their environment, much as players of the game do when they experience it at Behavior Lab.

Each agent had eight memory slots initially filled with random behaviors. With each interaction, an agent would pick a behavior from its memory and apply it. If the interaction resulted in a positive outcome for the agent (unreciprocated nose-thumbing, or a successful rock-paper-scissors match), that behavior was copied to another slot in memory. If the behavior resulted in any other outcome, that memory slot was overwritten with a new random behavior. Agents were designed to move towards other agents with whom they’d interacted positively, and away from those with whom interaction had failed.

At first, the simulation didn’t work very well. Aggressive behavior (nose-thumbing), was too seductive for the dim-witted agents and stable social groups never formed. In order to get the agents to behave a little more like people, I had to add a little extra subtlety. This came in the form of two new rules.

The first rule was that if an Agent A was aggressive to agent B, B would remember that fact and be aggressive back at the next opportunity. This captures the idea of ‘Tit for Tat’—a strategy that has proved very successful in Prisoner’s Dilemma tournaments.

The second rule was that if A and B had a successful match of rock, paper, or scissors, they’d both remember it and try for the same topic of conversation next time. This gave the agents a chance to reinforce positive relationships.

These two rules together did the trick and produced a somewhat mesmeric simulation. You can see it here, by just clicking on the first simulation button that appears. (Sadly, WordPress isn’t enthusiastic about supporting applets, otherwise I would have included it in this blog. Also, note that you’ll need Java installed for this to work. If you don’t have Java, let me know. I’m thinking of writing an HTML5 version and am keen to know whether that would make life easier for people.) In this simulation, the colors red, green, and blue take the place of rock, paper and scissors. The color gray takes the place of nose-thumbing.

However, once I’d finished the simulation, it occurred to me that I’d only scratched the surface of what could be demonstrated with this approach. I could go further, do more, and start saying something really meaningful. Better still, the tools to achieve it were already in my hands! However, I’ve promised myself that each one of these postings will be short and readable by people with day jobs, so in order to discover what I did next, you’ll have to join me for Episode Four.

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