Evolvability and redundancy in shared grammar evolution

Los Alamitos, C

A Naturalist Reconstruction of Minimalist and Evolutionary Biolinguistics

Kinsella & Marcus (2009; K&M) argue that considerations of biological evolution invalidate the picture of optimal language design put forward under the rubric of the minimalist program (Chomsky 1993 et seq.), but in this article it will be pointed out that K&M’s objection is undermined by (i) their misunderstanding of minimalism as imposing an aprioristic presumption of optimality and (ii) their failure to discuss the third factor of language design. It is proposed that the essence of K&M’s suggestion be reconstructed as the sound warning that one should refrain from any preconceptions about the object of inquiry, to which K&M commit themselves based on their biased view of evolution. A different reflection will be cast on the current minimalist literature, arguably along the lines K&M envisaged but never completed, converging on a recommendation of methodological (and, in a somewhat unconventional sense, metaphysical) naturalism

A rewriting grammar for heat exchanger network structure evolution with stream splitting

The design of cost optimal heat exchanger networks is a difficult optimisation problem due both to the nonlinear models required and also the combinatorial size of the search space. When stream splitting is considered, the combinatorial aspects make the problem even harder. This paper describes the implementation of a two level evolutionary algorithm based on a string rewriting grammar for the evolution of the heat exchanger network structure. A biological analogue of genotypes and phenotypes is used to describe structures and specific solutions respectively. The top level algorithm evolves structures while the lower level optimises specific structures. The result is a hybrid optimisation procedure which can identify the best structures including stream splitting. Case studies from the literature are presented to demonstrate the capabilities of the novel procedure

The Mind is Not (Just) a System of Modules Shaped (Just) by Natural Selection

[First paragraph]. 1. Did the Mind Evolve by Natural Selection? Of course our minds and brains evolved by natural selection! They aren’t the result of divine intervention or fabrication by space aliens. Nor are they solely products of drift or any other naturalistic alternative to selection. That natural selection profoundly "shaped" the mind and brain is accepted by both by evolutionary psychologists and virtually all of their most vigorous critics

Neural redundancy and its relation to neural reuse

Evidence of the pervasiveness of neural reuse in the human brain has forced a revision of the standard conception of modularity in the cognitive sciences. One persistent line of argument against such revision, however, draws from a large body of experimental literature attesting to the existence of cognitive dissociations. While numerous rejoinders to this argument have been offered over the years, few have grappled seriously with the phenomenon. This paper offers a fresh perspective. It takes the dissociations seriously, on the one hand, while affirming that traditional modularities of mind do not do justice to the evidence of neural reuse, on the other. The key to the puzzle is neural redundancy. The paper offers both a philosophical analysis of the relation between reuse and redundancy, as well as a plausible solution to the problem of dissociations

‘The uses of ethnography in the science of cultural evolution’. Commentary on Mesoudi, A., Whiten, A. and K. Laland ‘Toward a unified science of cultural evolution’

There is considerable scope for developing a more explicit role for ethnography within the research program proposed in the article. Ethnographic studies of cultural micro-evolution would complement experimental approaches by providing insights into the “natural” settings in which cultural behaviours occur. Ethnography can also contribute to the study of cultural macro-evolution by shedding light on the conditions that generate and maintain cultural lineages

Coping with evolution in information systems: a database perspective

Business organisations today are faced with the complex problem of dealing with evolution in their software information systems. This effectively concerns the accommodation and facilitation of change, in terms of both changing user requirements and changing technological requirements. An approach that uses the software development life-cycle as a vehicle to study the problem of evolution is adopted. This involves the stages of requirements analysis, system specification, design, implementation, and finally operation and maintenance. The problem of evolution is one requiring proactive as well as reactive solutions for any given application domain. Measuring evolvability in conceptual models and the specification of changing requirements are considered. However, even "best designs" are limited in dealing with unanticipated evolution, and require implementation phase paradigms that can facilitate an evolution correctly (semantic integrity), efficiently (minimal disruption of services) and consistently (all affected parts are consistent following the change). These are also discussedComputingM. Sc. (Information Systems

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

From genotypes to organisms: State-of-the-art and perspectives of a cornerstone in evolutionary dynamics

Understanding how genotypes map onto phenotypes, fitness, and eventually organisms is arguably the next major missing piece in a fully predictive theory of evolution. We refer to this generally as the problem of the genotype-phenotype map. Though we are still far from achieving a complete picture of these relationships, our current understanding of simpler questions, such as the structure induced in the space of genotypes by sequences mapped to molecular structures, has revealed important facts that deeply affect the dynamical description of evolutionary processes. Empirical evidence supporting the fundamental relevance of features such as phenotypic bias is mounting as well, while the synthesis of conceptual and experimental progress leads to questioning current assumptions on the nature of evolutionary dynamics-cancer progression models or synthetic biology approaches being notable examples. This work delves into a critical and constructive attitude in our current knowledge of how genotypes map onto molecular phenotypes and organismal functions, and discusses theoretical and empirical avenues to broaden and improve this comprehension. As a final goal, this community should aim at deriving an updated picture of evolutionary processes soundly relying on the structural properties of genotype spaces, as revealed by modern techniques of molecular and functional analysis.Comment: 111 pages, 11 figures uses elsarticle latex clas