Architectural design is typically limited by the constraints imposed by physical space. If and when opportunities to attenuate or extinguish these limits arise, should they be seized? Here it is argued that the limiting influence of spatial embedding should not be regarded as a frustrating tyranny to be escaped wherever possible, but as a welcome enabling constraint to be leveraged. Examples from the natural world are presented, and an appeal is made to some recent results on complex systems and measures (...) of interaction complexity. (shrink)

What is it about simulation models that has led some practitioners to treat them as potential sources of empirical data on the real-world systems being simulated; that is, to treat simulations as ‘artificial worlds’within which to perform computational ‘experiments’? Here we use the work of Richard Levins as a starting point in identifying the appeal of this model building strategy, and proceed to account for why this appeal is strongest for computational modellers. This analysis suggests a perspective on simulation modelling (...) that makes room for ‘artificial worlds’ as legitimate science without having to accept that they should be treated as sources of empirical data. (shrink)

The teleological language in the target article is ill-advised, as it obscures the question of whether ecological and cultural inheritances are directed or random. Laland et al. present a very broad palette of explanatory possibilities; evolutionary simulation models could help narrow down the processes important in a particular case. Examples of such models are offered in the areas of language change and the Baldwin effect.

Evolutionary activity statistics and their visualization are introduced, and their motivation is explained. Examples of their use are described, and their strengths and limitations are discussed. References to more extensive or general accounts of these techniques are provided.

Many natural and technological systems are complex, with organizational structures that exhibit characteristic patterns but defy concise description. One effective approach to analyzing such systems is in terms of repeated topological motifs. Here, we extend the motif concept to characterize the dynamic behavior of complex systems by introducing developmental motifs, which capture patterns of system growth. As a proof of concept, we use developmental motifs to analyze the developmental cell lineage of the nematode Caenorhabditis elegans, revealing a new perspective on (...) its complex structure. We use a family of computational models to explore how biases arising from the dynamics of the developmental gene network, as well as spatial and temporal constraints acting on development, contribute to this complex organization. © 2010 Wiley Periodicals, Inc. Complexity 16: 48‐57, 2011. (shrink)

A working assumption that processes of natural and cultural evolution have tailored the mind to fit the demands and structure of its environment begs the question: how are we to characterize the structure of cognitive environments? Decision problems faced by real organisms are not like simple multiple-choice examination papers. For example, some individual problems may occur much more frequently than others, whilst some may carry much more weight than others. Such considerations are not taken into account when (i) the performance (...) of candidate cognitive mechanisms is assessed by employing a simple accuracy metric that is insensitive to the structure of the decision-maker's environment, and (ii) reason is defined as the adherence to internalist prescriptions of classical rationality. Here we explore the impact of frequency and significance structure on the performance of a range of candidate decision-making mechanisms. We show that the character of this impact is complex, since structured environments demand that decision-makers trade off general performance against performance on important subsets of test items. As a result, environment structure obviates internalist criteria of rationality. Failing to appreciate the role of environment structure in shaping cognition can lead to mischaracterising adaptive behavior as irrational. (shrink)