Ecolab[9, 7] is a model system of an ecology that attempts to understand evolutionary processes. It makes a particular assumption about the embryology, or genotype-phenotype map in order to generate the novel ecological interaction coefficients from the novel genotypes as they arise through mutation. The Eco-Tierra project[7] examines this assumption using Tierra[2] as a model ecosystem, which has an implicitly defined embryology.

In the original specification of the Ecolab model, spatial variation of the system's variables was included, with an additional migration operator introduced proportional to the divergence of the species density. Suitably discretized, the model then consists of a number of cells, each running the non-spatial Ecolab model, linked together by the migration operator. This paper reports on the implementation of such a cellular Ecolab.

In a project the author is involved with, the run time efficiency of Tierra has become of paramount importance. Whilst some optimisations can be applied to the Tierra code itself, the speedup is at most 2--3 times, with no benefits from vectorisation or parallelisation being realised due to the structure of the code. A new formulation of Tierra is proposed which gains the computational efficiency of a population model, without sacrificing the advantages of an individual model. This new formulation can take advantage of parallelism when available. In some preliminary tests, the new code is up to three orders of magnitude faster than Tierra.

The paper presents an evolutionary dynamic economic model based on von-Neumann's work. Von Neuman's balanced growth solution is shown to be the long time average behaviour of the dynamic system, and that growth is found to be constrained by the productivities of key processes, called the generators of the economy. Some discussion is given about how to implement this model using the Ecolab modeling tool.

Numerous definitions for complexity have been proposed over the last half century, with little consensus achieved on how to use the term. A definition of complexity is supplied here that is closely related to the Kolmogorov Complexity and Shannon Entropy measures widely used as complexity measures, yet addresses a number of concerns raised against these measures. However, the price of doing this is to introduce context dependence into the definition of complexity. It is argued that such context dependence is an inherent property of complexity, and related concepts such as entropy and emergence. Scientists are uncomfortable with such context dependence, which smacks of subjectivity, and this is perhaps the reason why little agreement has been found on the meaning of these terms. 1 The problem of Complexity In the last 15 years, the study of Complex Systems has emerged as a recognised field in its own right, although a good definition of what a complex system