Hyper-learning for population-based incremental learning in dynamic environments

This article is posted here here with permission from IEEE - Copyright @ 2009 IEEEThe population-based incremental learning (PBIL) algorithm is a combination of evolutionary optimization and competitive learning. Recently, the PBIL algorithm has been applied for dynamic optimization problems. This paper investigates the effect of the learning rate, which is a key parameter of PBIL, on the performance of PBIL in dynamic environments. A hyper-learning scheme is proposed for PBIL, where the learning rate is temporarily raised whenever the environment changes. The hyper-learning scheme can be combined with other approaches, e.g., the restart and hypermutation schemes, for PBIL in dynamic environments. Based on a series of dynamic test problems, experiments are carried out to investigate the effect of different learning rates and the proposed hyper-learning scheme in combination with restart and hypermutation schemes on the performance of PBIL. The experimental results show that the learning rate has a significant impact on the performance of the PBIL algorithm in dynamic environments and that the effect of the proposed hyper-learning scheme depends on the environmental dynamics and other schemes combined in the PBIL algorithm.The work by Shengxiang Yang was supported by the Engineering and Physical Sciences Research Council (EPSRC) of the United Kingdom under Grant EP/E060722/1

Genetic algorithms with memory- and elitism-based immigrants in dynamic environments

Copyright @ 2008 by the Massachusetts Institute of TechnologyIn recent years the genetic algorithm community has shown a growing interest in studying dynamic optimization problems. Several approaches have been devised. The random immigrants and memory schemes are two major ones. The random immigrants scheme addresses dynamic environments by maintaining the population diversity while the memory scheme aims to adapt genetic algorithms quickly to new environments by reusing historical information. This paper investigates a hybrid memory and random immigrants scheme, called memory-based immigrants, and a hybrid elitism and random immigrants scheme, called elitism-based immigrants, for genetic algorithms in dynamic environments. In these schemes, the best individual from memory or the elite from the previous generation is retrieved as the base to create immigrants into the population by mutation. This way, not only can diversity be maintained but it is done more efficiently to adapt genetic algorithms to the current environment. Based on a series of systematically constructed dynamic problems, experiments are carried out to compare genetic algorithms with the memory-based and elitism-based immigrants schemes against genetic algorithms with traditional memory and random immigrants schemes and a hybrid memory and multi-population scheme. The sensitivity analysis regarding some key parameters is also carried out. Experimental results show that the memory-based and elitism-based immigrants schemes efficiently improve the performance of genetic algorithms in dynamic environments.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of the United Kingdom under Grant EP/E060722/01

Evolutionary computation in dynamic and uncertain environments

This book can be accessed from the link below - Copyright @ 2007 Springer-Verla

The diverse broad-band light-curves of Swift GRBs reproduced with the cannonball model

Two radiation mechanisms, inverse Compton scattering (ICS) and synchrotron radiation (SR), suffice within the cannonball (CB) model of long gamma ray bursts (LGRBs) and X-ray flashes (XRFs) to provide a very simple and accurate description of their observed prompt emission and afterglows. Simple as they are, the two mechanisms and the burst environment generate the rich structure of the light curves at all frequencies and times. This is demonstrated for 33 selected Swift LGRBs and XRFs, which are well sampled from early until late time and faithfully represent the entire diversity of the broad-band light curves of Swift LGRBs and XRFs. Their prompt gamma-ray and X-ray emission is dominated by ICS of `glory' light. During their fast decline phase, ICS is taken over by SR, which dominates their broad-band afterglow. The pulse shape and spectral evolution of the gamma-ray peaks and the early-time X-ray flares, and even the delayed optical `humps' in XRFs, are correctly predicted. The `canonical' and non-canonical X-ray light curves and the chromatic behaviour of the broad-band afterglows are well reproduced. In particular, in canonical X-ray light curves, the initial fast decline and rapid softening of the prompt emission, the transition to the plateau phase, the subsequent gradual steepening of the plateau to an asymptotic power-law decay, and the transition from chromatic to achromatic behaviour of the light curves agrees well with those predicted by the CB model. The Swift early-time data on XRF 060218 are inconsistent with a black-body emission from a shock break-out through a stellar envelope. Instead, they are well described by ICS of glory light by a jet breaking out from SN2006aj.Comment: Accepted for publication in The Astrophysical Journal. 63 pages, 10 (multiple) figure

Molecular abundances in OMC-1: The chemical composition of interstellar molecular clouds and the influence of massive star formation

We present here an investigation of the chemical composition of the various regions in the core of the Orion molecular cloud (OMC-1) based on results from the Caltech Owens Valley Radio Observatory (OVRO) millimeter-wave spectral line survey (Sutton et al.; Blake et al.). This survey covered a 55 GHz interval in the 1.3 mm (230 GHz) atmospheric window and contained emission from over 800 resolved spectral features. Of the 29 identified species 14 have a sufficient number of detected transitions to be investigated with an LTE "rotation diagram" technique, in which large numbers of lines are used to estimate both the rotational excitation and the overall abundance. The rotational temperatures and column densities resulting from these fits have then been used to model the emission from those remaining species which either have too few lines or which are too weak to be so analyzed. When different kinematic sources of emission are blended to produce a single feature, Gaussian fits have been used to derive the individual contributions to the total line profile. The uniformly calibrated data in the unique and extensive Caltech spectral line survey lead to accurate estimates of the chemical and physical parameters of the Orion molecular cloud, and place significant constraints on models of interstellar chemistry. A global analysis of the observed abundances shows that the markedly different chemical compositions of the kinematically and spatially distinct Orion subsources may be interpreted in the framework of an evolving, initially quiescent, gas-phase chemistry influenced by the process of massive star formation. The chemical composition of the extended Orion cloud complex is similar to that found in a number of other objects, but the central regions of OMC-1 have had their chemistry selectively altered by the radiation and high-velocity outflow from the young stars embedded deep within the interior of the molecular cloud. Specifically, the extended ridge clouds are inferred to have a low (subsolar) gas-phase oxygen content from the prevalence of reactive carbon-rich species like CN, CCH, and C_3H_2 also found in more truly quiescent objects such as TMC-1. The similar abundances of these and other simple species in clouds like OMC-1, Sgr B2, and TMC-1 lend support to gas-phase ion-molecule models of interstellar chemistry, but grain processes may also play a significant role in maintaining the overall chemical balance in such regions through selective depletion mechanisms and grain mantle processing. In contrast, the chemical compositions of the more turbulent plateau and hot core components of OMC-1 are dominated by high-temperature, shock-induced gas and grain surface neutral-neutral reaction processes. The high silicon/sulfur oxide and water content of the plateau gas is best modeled by fast shock disruption of smaller grain cores to release the more refractory elements followed by a predominantly neutral chemistry in the cooling postshock regions, while a more passive release of grain mantle products driven toward kinetic equilibrium most naturally explains the prominence of fully hydrogenated N-containing species like HCN, NH_3 , CH_3CN, and C_2H_5CN in the hot core. The clumpy nature of the outflow is illustrated by the high-velocity emission observed from easily decomposed molecules such as H_2CO. Areas immediately adjacent to the shocked core in which the cooler, ion-rich gas of the surrounding molecular cloud is mixed with water/oxygen rich gas from the plateau source are proposed to give rise to the enhanced abundances of complex internal rotors such as CH_30H, HCOOCH_3 , and CH_30CH_3 whose line widths are similar to carbon-rich species such as CN and CCH found in the extended ridge, but whose rotational temperatures are somewhat higher and whose spatial extents are much more compact

A memetic algorithm with adaptive hill climbing strategy for dynamic optimization problems

Copyright @ Springer-Verlag 2008Dynamic optimization problems challenge traditional evolutionary algorithms seriously since they, once converged, cannot adapt quickly to environmental changes. This paper investigates the application of memetic algorithms, a class of hybrid evolutionary algorithms, for dynamic optimization problems. An adaptive hill climbing method is proposed as the local search technique in the framework of memetic algorithms, which combines the features of greedy crossover-based hill climbing and steepest mutation-based hill climbing. In order to address the convergence problem, two diversity maintaining methods, called adaptive dual mapping and triggered random immigrants, respectively, are also introduced into the proposed memetic algorithm for dynamic optimization problems. Based on a series of dynamic problems generated from several stationary benchmark problems, experiments are carried out to investigate the performance of the proposed memetic algorithm in comparison with some peer evolutionary algorithms. The experimental results show the efficiency of the proposed memetic algorithm in dynamic environments.This work was supported by the National Nature Science Foundation of China (NSFC) under Grant Nos. 70431003 and 70671020, the National Innovation Research Community Science Foundation of China under Grant No. 60521003, and the National Support Plan of China under Grant No. 2006BAH02A09 and the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/01

Small and mighty: adaptation of superphylum Patescibacteria to groundwater environment drives their genome simplicity.

BackgroundThe newly defined superphylum Patescibacteria such as Parcubacteria (OD1) and Microgenomates (OP11) has been found to be prevalent in groundwater, sediment, lake, and other aquifer environments. Recently increasing attention has been paid to this diverse superphylum including > 20 candidate phyla (a large part of the candidate phylum radiation, CPR) because it refreshed our view of the tree of life. However, adaptive traits contributing to its prevalence are still not well known.ResultsHere, we investigated the genomic features and metabolic pathways of Patescibacteria in groundwater through genome-resolved metagenomics analysis of > 600 Gbp sequence data. We observed that, while the members of Patescibacteria have reduced genomes (~ 1 Mbp) exclusively, functions essential to growth and reproduction such as genetic information processing were retained. Surprisingly, they have sharply reduced redundant and nonessential functions, including specific metabolic activities and stress response systems. The Patescibacteria have ultra-small cells and simplified membrane structures, including flagellar assembly, transporters, and two-component systems. Despite the lack of CRISPR viral defense, the bacteria may evade predation through deletion of common membrane phage receptors and other alternative strategies, which may explain the low representation of prophage proteins in their genomes and lack of CRISPR. By establishing the linkages between bacterial features and the groundwater environmental conditions, our results provide important insights into the functions and evolution of this CPR group.ConclusionsWe found that Patescibacteria has streamlined many functions while acquiring advantages such as avoiding phage invasion, to adapt to the groundwater environment. The unique features of small genome size, ultra-small cell size, and lacking CRISPR of this large lineage are bringing new understandings on life of Bacteria. Our results provide important insights into the mechanisms for adaptation of the superphylum in the groundwater environments, and demonstrate a case where less is more, and small is mighty