Improving the adaptability of simulated evolutionary swarm robots in dynamically changing environments

One of the important challenges in the field of evolutionary robotics is the development of systems that can adapt to a changing environment. However, the ability to adapt to unknown and fluctuating environments is not straightforward. Here, we explore the adaptive potential of simulated swarm robots that contain a genomic encoding of a bio-inspired gene regulatory network (GRN). An artificial genome is combined with a flexible agent-based system, representing the activated part of the regulatory network that transduces environmental cues into phenotypic behaviour. Using an artificial life simulation framework that mimics a dynamically changing environment, we show that separating the static from the conditionally active part of the network contributes to a better adaptive behaviour. Furthermore, in contrast with most hitherto developed ANN-based systems that need to re-optimize their complete controller network from scratch each time they are subjected to novel conditions, our system uses its genome to store GRNs whose performance was optimized under a particular environmental condition for a sufficiently long time. When subjected to a new environment, the previous condition-specific GRN might become inactivated, but remains present. This ability to store 'good behaviour' and to disconnect it from the novel rewiring that is essential under a new condition allows faster re-adaptation if any of the previously observed environmental conditions is reencountered. As we show here, applying these evolutionary-based principles leads to accelerated and improved adaptive evolution in a non-stable environment

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

Evolution of Robustness and Plasticity under Environmental Fluctuation: Formulation in terms of Phenotypic Variances

The characterization of plasticity, robustness, and evolvability, an important issue in biology, is studied in terms of phenotypic fluctuations. By numerically evolving gene regulatory networks, the proportionality between the phenotypic variances of epigenetic and genetic origins is confirmed. The former is given by the variance of the phenotypic fluctuation due to noise in the developmental process; and the latter, by the variance of the phenotypic fluctuation due to genetic mutation. The relationship suggests a link between robustness to noise and to mutation, since robustness can be defined by the sharpness of the distribution of the phenotype. Next, the proportionality between the variances is demonstrated to also hold over expressions of different genes (phenotypic traits) when the system acquires robustness through the evolution. Then, evolution under environmental variation is numerically investigated and it is found that both the adaptability to a novel environment and the robustness are made compatible when a certain degree of phenotypic fluctuations exists due to noise. The highest adaptability is achieved at a certain noise level at which the gene expression dynamics are near the critical state to lose the robustness. Based on our results, we revisit Waddington's canalization and genetic assimilation with regard to the two types of phenotypic fluctuations.Comment: 23 pages 11 figure

Diversity, stability and regional growth in the U.S. (1975-2002)

This paper summarizes the theoretical arguments from evolutionary theory and ecological economics to put the trade-off between regional economic diversity and regional economic growth on stronger theoretical foundations. Hypotheses are tested using an empirical model that links regional economic diversity to stability and growth using data on 177 BEA areas of the continental United States during the period (1975-2002).evolutionary economics, ecological economies, diversity, stbility, regional growth

Conceptualising Cluster Evolution: Beyond the Life-Cycle Model?

Although the literature on the evolution of industrial clusters is not vast, a preferred approach has already become evident, based around the idea of a cluster 'life-cycle'. This approach has several limitations. In this paper we explore a different conception of cluster evolution drawing on the 'adaptive cycle' model that has been developed in evolutionary ecology. Using this model, cluster evolution is viewed as an adaptive process with different possible outcomes based on episodic interactions of nested systems. Though not without limitations, this approach offers greater scope as a framework for shaping the research agenda into the evolution of clusters.Clusters, Evolution, Life-cycle model, Complex systems, Adaptive cycle model

Economic resilience : including a case study of the global transition network

This paper explores the dynamic properties of organisms and ecosystems that make them so resilient and capable of adapting to changing circumstances, allowing them to maintain an overall condition of coherence, wholeness and health while living in balance within the resources of the planet. Key principles of resilient ecological systems are explored including: self-regulation; positive and negative feedback; diversity; scale and context; cooperation; emergence and novelty; and ecological tipping points. In contrast, market based economic systems can produce unstable growth with unintended destruction of cultural and species diversity and homogenisation of global life-styles. The paper re-examines fundamental economic principles using insights from biological evolution and ecosystem dynamics to establish a foundation for more resilient economies. This involves experimenting with different models in different communities to find patterns of sustainable production and exchange appropriate to local regions. Fundamental steps in this direction include the emergence of self-organising local communities based on creative experimentation, re-localisation of core sectors of the economy (food, energy, health and education), evolution of local currencies and banking practices that support local enterprise and investment in green technologies, stimulation of decentralised renewable energy networks and economic reform aligned with ecological principles. The Transition Network provides a case study of an international community based movement that has been experimenting with putting some of these principles into practice at the local level. The aim of the Transition Network is to support community led responses to peak oil and climate change, building resilience and well-being. The concept of ecological resilience and its application to local economy is hard wired into the values and emerging structure of the network of transition communities across the globe. The movement started in the UK in 2005 and there are now over 1000 Transition initiatives spanning 34 countries across the world. Many attribute the success and phenomenal growth of the Transition Network to its emerging holographic structure that mimics cell growth within living organisms. Growing a more resilient food system in the face of the twin challenges of natural resource scarcity and climate change is central to the Transition movement. A set of principles for a post carbon resilient food economy in the UK are offered. These include an 80% cut in carbon emission in the food sector by 2050, agricultural diversification, prioritization of farming methods that establish and enhance carbon sinks, phasing out of dependence on fossil fuels in food growing, processing and distribution, promoting access to nutritious and affordable food, as well as promoting greater access to land for growing food in urban and peri-urban areas. Practical examples of Transition related projects in the food sector are presented across the following themes: access to land, low carbon production methods, food distribution systems, health and community gardens and orchards, and collaborative ownership models

Evolution of Supply Chain Collaboration: Implications for the Role of Knowledge

Increasingly, research across many disciplines has recognized the shortcomings of the traditional “integration prescription” for inter-organizational knowledge management. This research conducts several simulation experiments to study the effects of different rates of product change, different demand environments, and different economies of scale on the level of integration between firms at different levels in the supply chain. The underlying paradigm shifts from a static, steady state view to a dynamic, complex adaptive systems and knowledge-based view of supply chain networks. Several research propositions are presented that use the role of knowledge in the supply chain to provide predictive power for how supply chain collaborations or integration should evolve. Suggestions and implications are suggested for managerial and research purposes