Complexity Theory, Adaptation, and Administrative Law

Recently, commentators have applied insights from complexity theory to legal analysis generally and to administrative law in particular. This Article focuses on one of the central problems that complexity. theory addresses, the importance and mechanisms of adaptation within complex systems. In Part I, the Article uses three features of complex adaptive systems-emergence from self-assembly, nonlinearity, and sensitivity to initial conditions-and explores the extent to which they may add value as a matter of positive analysis to the understanding of change within legal systems. In Part H, the Article focuses on three normative claims in public law scholarship that depend explicitly or implicitly on notions of adaptation: that states offer advantages over the federal government because experimentation can make them more adaptive, that federal agencies should themselves become more experimentalist using the tool of adaptive management, and that administrative agencies shou Id adopt collaborative mechanisms in policymaking. Using two analytic tools found in the complexity literature, the genetic algorithm and evolutionary game theory, the Article tests the extent to which these three normative claims are borne out

Simulation Models of the Evolution of Cooperation as Proofs of Logical Possibilities. How Useful Are They?

This paper discusses critically what simulation models of the evolution of cooperation can possibly prove by examining Axelrod’s “Evolution of Cooperation” (1984) and the modeling tradition it has inspired. Hardly any of the many simulation models in this tradition have been applicable empirically. Axelrod’s role model suggested a research design that seemingly allowed to draw general conclusions from simulation models even if the mechanisms that drive the simulation could not be identified empirically. But this research design was fundamentally flawed. At best such simulations can claim to prove logical possibilities, i.e. they prove that certain phenomena are possible as the consequence of the modeling assumptions built into the simulation, but not that they are possible or can be expected to occur in reality. I suggest several requirements under which proofs of logical possibilities can nevertheless be considered useful. Sadly, most Axelrod-style simulations do not meet these requirements. It would be better not to use this kind of simulations at all

Does Language Determine Our Scientific Ideas?

SummaryThis paper argues that the influence of language on science, philosophy and other field is mediated by communicative practices. Where communications is more restrictive, established linguistic structures exercise a tighter control over innovations and scientifically motivated reforms of language. The viewpoint here centers on the thesis that argumentation is crucial in the understanding and evaluation of proposed reforms and that social practices which limit argumentation serve to erode scientific objectivity. Thus, a plea is made for a sociology of scientific belief designed to understand and insure social‐institutional conditions of the possibility of knowledge and its growth. A chief argument draws on work of Axelrod concerning the evolution of cooperation

Asymptotic Behavior of Strategies in the Repeated Prisoner's Dilemma Game in the Presence of Errors

We examine the asymptotic behavior of a finite, but error-prone population, whose agents can choose one of ALLD (always defect), ALLC (always cooperate), or Pavlov (repeats the previous action if the opponent cooperated and changes action otherwise) to play the repeated Prisoner's Dilemma. A novelty of the study is that it allows for three types of errors that affect agents' strategies in distinct ways: (a) implementation errors, (b) perception errors of one's own action, and (c) perception errors of the opponent's action. We also derive numerical results based on the payoff matrix used in the tournaments of Axelrod (1984). Strategies' payoffs are monitored as the likelihood of committing errors increases from zero to one, which enables us to provide a taxonomy of best response strategies. We find that for some range of error levels, a unique best response (i.e. a dominant strategy) exists. In all other, the population composition can vary based on the proportion of each strategist's type and/or the payoffs of the matrix. Overall, our results indicate that the emergence of cooperation is considerably weak at most error levels

How Models Fail. A Critical Look at the History of Computer Simulations of the Evolution of Cooperation

Simulation models of the Reiterated Prisoner's Dilemma have been popular for studying the evolution of cooperation since more than 30 years now. However, there have been practically no successful instances of empirical application of any of these models. At the same time this lack of empirical testing and confirmation has almost entirely been ignored by the modelers community. In this paper, I examine some of the typical narratives and standard arguments with which these models are justified by their authors despite the lack of empirical validation. I find that most of the narratives and arguments are not at all compelling. None the less they seem to serve an important function in keeping the simulation business running despite its empirical shortcomings

Evolutionary Game Theory

Articl

Analyzing Social Network Structures in the Iterated Prisoner's Dilemma with Choice and Refusal

The Iterated Prisoner's Dilemma with Choice and Refusal (IPD/CR) is an extension of the Iterated Prisoner's Dilemma with evolution that allows players to choose and to refuse their game partners. From individual behaviors, behavioral population structures emerge. In this report, we examine one particular IPD/CR environment and document the social network methods used to identify population behaviors found within this complex adaptive system. In contrast to the standard homogeneous population of nice cooperators, we have also found metastable populations of mixed strategies within this environment. In particular, the social networks of interesting populations and their evolution are examined.Comment: 37 pages, uuencoded gzip'd Postscript (1.1Mb when gunzip'd) also available via WWW at http://www.cs.wisc.edu/~smucker/ipd-cr/ipd-cr.htm

Exploring the cooperative regimes in a model of agents without memory or "tags": indirect reciprocity vs. selfish incentives

The self-organization in cooperative regimes in a simple mean-field version of a model based on "selfish" agents which play the Prisoner's Dilemma (PD) game is studied. The agents have no memory and use strategies not based on direct reciprocity nor 'tags'. Two variables are assigned to each agent $i$ at time $t$, measuring its capital $C(i;t)$ and its probability of cooperation $p(i;t)$. At each time step $t$ a pair of agents interact by playing the PD game. These 2 agents update their probability of cooperation $p(i)$ as follows: they compare the profits they made in this interaction $\delta C(i;t)$ with an estimator $\epsilon(i;t)$ and, if $\delta C(i;t) \ge \epsilon(i;t)$, agent $i$ increases its $p(i;t)$ while if $\delta C(i;t) < \epsilon(i;t)$ the agent decreases $p(i;t)$. The 4!=24 different cases produced by permuting the four Prisoner's Dilemma canonical payoffs 3, 0, 1, and 5 - corresponding,respectively, to $R$ (reward), $S$ (sucker's payoff), $T$ (temptation to defect) and $P$ (punishment) - are analyzed. It turns out that for all these 24 possibilities, after a transient,the system self-organizes into a stationary state with average equilibrium probability of cooperation $\bar{p}_\infty$ = constant $> 0$.Depending on the payoff matrix, there are different equilibrium states characterized by their average probability of cooperation and average equilibrium per-capita-income ($\bar{p}_\infty,\bar{\delta C}_\infty$).Comment: 11 pages, 5 figure