This is another cool, indepth article published on Gamasutra. Skip Cole wrote this one, with the full title of Modeling Opinion Flow in Humans Using Boids Algorithm & Social Network Analysis.
Do you like the idea that you, me, our friends and our communities can all be reduced to a numerical estimation of our opinions, and our likely behavior based on them? 😀 Yes, I am again getting at the point that games and simulations are not just games and simulations – that they can be useful tools for studying, analyzing and predicting the “real” world. Indeed, that I think we will hone and polish them into the best of all possible tools for doing those things.
Here’s his introduction, which lays out what he’s talking about. The other 7 and a half pages actually detail it and explain it. If you’re interested in algorithms, games or simply how society works, you’ll be interested in all of this.
Given the opinions and desires of a non-player character (actors), it is possible to devise a cost-benefit calculation to decide what they are likely to do. This is a common problem in Game AI and much good work has already been done on this. But this supposes a fixed set of opinions (beliefs) in the actors. We would like to allow the actors to evolve and change their opinions over time, just as real people do. We also want to replicate the fact that while the opinions people hold are often understandable, they are not always rational. In this paper we introduce a methodology to do just this.
Modeling opinion flow is a big topic. People’s opinions are understandably multi-faceted and complex. Here we are saying dash to this complexity and reducing the decisions on one particular issue (the topic at hand) to one simple number. At the end of the day in our game universe, one supports King John, supports King Richard, or doesn’t particularly support anyone. If the bulk of the population supports King John, then his troops will receive more resources – and that is an effect that can be felt by King Richard1.
To perform our calculation, we are borrowing concepts from the Boids algorithm and from Social Network Analysis. This technique makes possible new types of conflict, such as a Public Relations battle, and can make concrete the ‘battle for hearts and minds.’
People’s opinions are influenced by events, but also by what they perceive to be the opinions of the people around them — people tend to believe what the people around them believe. The central analogy of this paper is that just as birds, fish, and other animals move their bodies in groups, humans move their opinions in groups2. Animals flock with their bodies. People flock in their opinions.
This technique can be applied to large populations or small populations. A large population example could be an entire population of a country and their support of a particular armed militia group. (If the player can reduce public support for the militia, its resources will decrease.) A small population example could be the actors around a key decision maker. (If the player can locate and change the opinions of the people around the decision maker, it will be possible to influence the decision maker.) Both examples will be explored here.
From a sidebar, here’s the bird example of Boid’s algorithm as it relates to the real world:
A bird that strays from the flock
will change its course to move
back toward the flock, even as the
flock may begin to veer toward it.
Most people feel uncomfortable if
their thinking is too far unaligned
from that of the group, and will try
(either by trying to change the
group or their own thinking) to
minimize that distance.