Book Review: The Stag Hunt and the Evolution of Social Structure

Brian Skyrms’ The Stag Hunt and the Evolution of Social Structure
addresses a subject lying at the intersection of the social sciences, philosophy, and evolutionary biology — how it is possible for social structures to emerge among populations of selfishly-acting individuals.
Using Rousseau’s example of a Stag Hunt, in which hunters face a decision between a less-risky but less-rewarding individual hunt forhare, or the more-risky but more-rewarding cooperative hunt for stag, Skyrms addresses three emergence of social structure as a product of three distinct effects:

  1. Location
  2. Signaling
  3. Association

Two chapters on each of these, plus an initial chapter introducing the stag hunt in elementary game-theoretic terms and describing its relevance to task at hand comprise this thoroughly enjoyable 150-page volume.
Readers like myself, who approach Skyrms’ book having read Axelrod’s The Evolution of Cooperation (or much of the voluminous literature it spawned), will hesitate at Skyrm’s choice of an assurance game (as the stag hunt is known in more prosaic circles) to model the growth of societal organization, preferring the familiar Prisoners’ Dilemma. Drawing from the political philosophy of Hume, from recent re-examination of John Maynard Smith‘s haystack model of the evolution of altruism, and from experimental economics, Skyrms’ justifies his choice in the first chapter.
Next, Skyrms discusses the relevance of Location, as egoistic actors repeatedly play divide-the-dollar against randomly-selected partners, and against neighbors arrayed on a lattice (as in, for example xlife). In the latter scenario, rapid movement toward a “just” equilibrium of even division is observed. Here, as throughout the book, Skyrms reinforces the timeless relevance of the theme he treats (in this chapter, with allusions to distributive justice discussion by Aristotle and Kant). This tactic runs the risk of distracting the reader, or making the writer seem like a name-dropper or pedant, but Skyrms uses it to very positive effect.
In the book’s next chapter, the dynamic behavior of local interactions in a stag hunt game among actors with different degrees and kinds of knowledge about the previous successes of others is discussed. This establishes a fuller picture of how the spatial structure affects the macro-level outcome. Since I read this chapter while waiting for a plane, I focussed less on the details and more on the main idea, which is that outcomes vary depending on the breadth of actors’ vision in considering whom to imitate, and on how small the set of neighbors with whom they may interact is. Here, the book’s first part ends.
Part II concerns Signals. The second of its two chapters considers the evolutionary dynamics of a stag hunt with “cheap talk” — a player’s strategy is not only whether to hunt stag or hare, but also what signal to send, and how to respond to signals he receives. The preceding chapter concerns itself with the development of social conventions, using as its first example language itself. How can language have come about, since the only way to communicate the extremely complex convention which speech represents is via speech itself? In considering this, Skyrms draws on David Lewis and presents in 14 pages a demonstration of how a system of logical inference can evolve, presupposing nothing (such as rationality, intentionality) that has not been observed at the level of a bacterium! That is cool.
The book’s third and final part concerns Association. In the first of its chapters, actors strategies are fixed (in contrast with the entire book until now, in which they evolve), and the interaction patterns among actors are allowed to evolve. Will groups of “friends” form? Will they be long-lived or ephemeral? How does this depend upon chance, length of memory of good times or of slights? Interesting reading, but by now one’s expectations are high! The final chapter considers simultaneously evolving strategies and interaction structures.
I enjoyed this book immensely. Its power derives from its inter-disciplinary foundation, its unflagging clarity of exposition, and the sheer magnitude of the question it tries (with some success!) to answer.
Inasmuch as the ubiquity of the computer, and the interconnectedness it affords so many people has focussed attention on the sorts of issues discussed in this small but important volume, Skyrms’ has produced a work directly relevant to most of those who are reading this (here is proof(?)).
Personally, I feel the value transcends mere pragmatic utility.

One Reply to “Book Review: The Stag Hunt and the Evolution of Social Structure”

  1. Chris, thanks for the review of what sounds like a delightfully polymath book. I may have to pick up a copy for the next long flight.
    *shameless plug*
    If anyone out there is interested in the questions of individual and group incentives with respect to network structure and attributes, I’ll be presenting a paper at the Sunbelt Social Network Conference on “The Tragedy of the Network”, and I can email a draft to anyone interested.

    The Tragedy of the Network
    In many social contexts, individuals choose a set of social interactions to maximize their private benefit, but the resulting social network structure is a public phenomenon that can affect all members of the network. Previous research (Lazer and Friedman 2005) has found that more efficient collaborative networks (e.g. small world networks) yield poor system-wide results. In this paper, using agent-based modeling and evolutionary algorithms, we take the efficiency of the network as endogenous to the system of problem-solvers, assuming that individuals choose a set of social interactions to maximize their private benefit. We then focus on the social success of actors in the resulting structure. Results show that while sparse networks perform better in the long run, individual actors will create a well-connected network through which information will flow rapidly, resulting in a poorly performing system. The “tragedy of the network” is that if everyone acts in their best interest, the resulting network will be worse for everyone. We discuss several examples of this stylized model from a variety of disciplines.

    Earlier related work here: