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

Towards the Evolution of Novel Vertical-Axis Wind Turbines

Renewable and sustainable energy is one of the most important challenges currently facing mankind. Wind has made an increasing contribution to the world's energy supply mix, but still remains a long way from reaching its full potential. In this paper, we investigate the use of artificial evolution to design vertical-axis wind turbine prototypes that are physically instantiated and evaluated under approximated wind tunnel conditions. An artificial neural network is used as a surrogate model to assist learning and found to reduce the number of fabrications required to reach a higher aerodynamic efficiency, resulting in an important cost reduction. Unlike in other approaches, such as computational fluid dynamics simulations, no mathematical formulations are used and no model assumptions are made.Comment: 14 pages, 11 figure

Identity Problems (An Interview with John B. Davis)

In this interview, Professor Davis discusses the evolution of his career and research interests as a philosopher-economist and gives his perspective on a number of important issues in the field. He argues that historians and methodologists of economics should be engaged in the practice of economics, and that historians should be more open to philosophical analysis of the content of economic ideas. He suggests that the history of recent economics is a particularly fruitful and important area for research exactly because it is an open-ended story that is very relevant to understanding the underlying concerns and concepts of contemporary economics. He discusses his engagement with heterodox economics schools, and their engagement with a rapidly changing mainstream economics. He argues that the theory of the individual is “the central philosophical issue in economics” and discusses his extensive contributions to the issue

Achieving Replicability: Is There Life for Our Experiments After Publication?

Metaheuristics are algorithmic schemes that ease the derivation of novel algorithms to solve optimization problems. These algorithms are typically approximated and stochastic, leading to the preeminence of experimentation as the mean of supporting claims in research and applications. However, the huge number of variants and parameters of most metaheuristics, the ambiguity of natural language used in papers, and the lack of widely accepted reporting standards threatens the replicability of those experiments. This problem, that has been identified in the literature by several authors, significantly hinders the construction of a complete and cohesive body of knowledge on the behavior of metaheuristics. This paper proposes a set of minimum information guidelines for reporting metaheuristic experiments, and an experiment description language that supports the meeting of those guidelines. By using this language, metaheuristic optimization experiments are described in a toolindependent and unambiguous way, while maintaining readability and succinctness. Those contributions pave the way for replication using different problem instances and parameters, bringing a new life to metaheuristic experiments after publication.Ministerio de Ciencia e Innovación TIN2009-07366Ministerio de Economía y Competitividad TIN2012-32273Junta de Andalucía P07-TIC-2533Junta de Andalucía TIC-590

From evolutionary computation to the evolution of things

Evolution has provided a source of inspiration for algorithm designers since the birth of computers. The resulting field, evolutionary computation, has been successful in solving engineering tasks ranging in outlook from the molecular to the astronomical. Today, the field is entering a new phase as evolutionary algorithms that take place in hardware are developed, opening up new avenues towards autonomous machines that can adapt to their environment. We discuss how evolutionary computation compares with natural evolution and what its benefits are relative to other computing approaches, and we introduce the emerging area of artificial evolution in physical systems

A checklist for choosing between R packages in ecology and evolution

The open source and free programming language R is a phenomenal mechanism to address a multiplicity of challenges in ecology and evolution. It is also a complex ecosystem because of the diversity of solutions available to the analyst. Packages for R enhance and specialize the capacity to explore both niche data/experiments and more common needs. However, the paradox of choice or how we select between many seemingly similar options can be overwhelming and lead to different potential outcomes. There is extensive choice in ecology and evolution between packages for both fundamental statistics and for more specialized domain‐level analyses. Here, we provide a checklist to inform these decisions based on the principles of resilience, need, and integration with scientific workflows for evidence. It is important to explore choices in any analytical coding environment—not just R—for solutions to challenges in ecology and evolution, and document this process because it advances reproducible science, promotes a deeper understand of the scientific evidence, and ensures that the outcomes are correct, representative, and robust.York University Librarie