Learning in evolutionary environments

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Group selection theories are now more sophisticated, but are they more predictive?

Human beings are unique among species in their ability to cooperate in large groups of genetically unrelated individuals, and in this book, Samuel Bowles and Herbert Gintis attempt to account for the origins of this ability. The authors specialize in the use of formal models and agent-based simulations in order to precisely specify their theories of cooperation, and they often draw on studies conducted in hunter gatherer societies and in experimental economic laboratories for evidence that they find relevant to evaluating these theories. The book is a valuable review of these anthropological and economic literatures, and a thorough showcase of the authors’ expert formal theorizing about how cooperation may have evolved. However, I often found myself disagreeing with the authors’ focus on group selection as an explanation for human cooperation, and with their views on how well the empirical findings provide support for group selectionist theories

Multi-perspective requirements engineering for networked business systems: a framework for pattern composition

How business and software analysts explore, document, and negotiate requirements for enterprise systems is critical to the benefits their organizations will eventually derive. In this paper, we present a framework for analysis and redesign of networked business systems. It is based on libraries of patterns which are derived from existing Internet businesses. The framework includes three perspectives: Economic value, Business processes, and Application communication, each of which applies a goal-oriented method to compose patterns. By means of consistency relationships between perspectives, we demonstrate the usefulness of the patterns as a light-weight approach to exploration of business ideas

The modern versus extended evolutionary synthesis : sketch of an intra-genomic gene's eye view for the evolutionary-genetic underpinning of epigenetic and developmental evolution

Studying the phenotypic evolution of organisms in terms of populations of genes and genotypes, the Modern Synthesis (MS) conceptualizes biological evolution in terms of 'inter-organismal' interactions among genes sitting in the different individual organisms that constitute a population. It 'black-boxes' the complex 'intra-organismic' molecular and developmental epigenetics mediating between genotypes and phenotypes. To conceptually integrate epigenetics and evo-devo into evolutionary theory, advocates of an Extended Evolutionary Synthesis (EES) argue that the MS's reductive gene-centrism should be abandoned in favor of a more inclusive organism-centered approach. To push the debate to a new level of understanding, we introduce the evolutionary biology of 'intra-genomic conflict' (IGC) to the controversy. This strategy is based on a twofold rationale. First, the field of IGC is both ‘gene-centered’ and 'intra-organismic' and, as such, could build a bridge between the gene-centered MS and the intra-organismic fields of epigenetics and evo-devo. And second, it is increasingly revealed that IGC plays a significant causal role in epigenetic and developmental evolution and even in speciation. Hence, to deal with the ‘discrepancy’ between the ‘gene-centered’ MS and the ‘intra-organismic’ fields of epigenetics and evo-devo, we sketch a conceptual solution in terms of ‘intra-genomic conflict and compromise’ – an ‘intra-genomic gene’s eye view’ that thinks in terms of intra-genomic ‘evolutionarily stable strategies’ (ESSs) among numerous and various DNA regions and elements – to evolutionary-genetically underwrite both epigenetic and developmental evolution, as such questioning the ‘gene-de-centered’ stance put forward by EES-advocates

Reusable Knowledge-based Components for Building Software Applications: A Knowledge Modelling Approach

In computer science, different types of reusable components for building software applications were proposed as a direct consequence of the emergence of new software programming paradigms. The success of these components for building applications depends on factors such as the flexibility in their combination or the facility for their selection in centralised or distributed environments such as internet. In this article, we propose a general type of reusable component, called primitive of representation, inspired by a knowledge-based approach that can promote reusability. The proposal can be understood as a generalisation of existing partial solutions that is applicable to both software and knowledge engineering for the development of hybrid applications that integrate conventional and knowledge based techniques. The article presents the structure and use of the component and describes our recent experience in the development of real-world applications based on this approach

Supporting organisational learning: an overview of the ENRICH approach

Traditional training separates learning from the work context in which the newly acquired knowledge is to be applied. This requires the worker themselves to apply imparted theoretical knowledge to knowledge in practice, a process that is grossly inefficient. The ENRICH approach builds on organisational learning theory to intertwine working and learning. The ENRICH methodology incorporates theories of learning at the individual, group and organisational level. Individual level learning is supported through the provision of semantically related resources to support problem reframing and to challenge assumptions. Group learning is supported through the evolution of domain concepts through work documents and representations linked to formal models of group knowledge, and the development of group practices and perspectives through enhanced sharing and collaboration. Organisational learning is supported through exposure to customs and conventions of other groups through shared best practices and knowledge models. The approach is being investigated in a range of industrial settings and applications

What are the true clusters?

Constructivist philosophy and Hasok Chang's active scientific realism are used to argue that the idea of "truth" in cluster analysis depends on the context and the clustering aims. Different characteristics of clusterings are required in different situations. Researchers should be explicit about on what requirements and what idea of "true clusters" their research is based, because clustering becomes scientific not through uniqueness but through transparent and open communication. The idea of "natural kinds" is a human construct, but it highlights the human experience that the reality outside the observer's control seems to make certain distinctions between categories inevitable. Various desirable characteristics of clusterings and various approaches to define a context-dependent truth are listed, and I discuss what impact these ideas can have on the comparison of clustering methods, and the choice of a clustering methods and related decisions in practice