Evolutionary computation and Wright's equation

AbstractIn this paper, Wright's equation formulated in 1931 is proven and applied to evolutionary computation. Wright's equation shows that evolution is doing gradient ascent in a landscape defined by the average fitness of the population. The average fitness W is defined in terms of marginal gene frequencies pi. Wright's equation is only approximately valid in population genetics, but it exactly describes the behavior of our univariate marginal distribution algorithm (UMDA). We apply Wright's equation to a specific fitness function defined by Wright. Furthermore we introduce mutation into Wright's equation and UMDA. We show that mutation moves the stable attractors from the boundary into the interior. We compare Wright's equation with the diversified replicator equation. We show that a fast version of Wright's equation gives very good results for optimizing a class of binary fitness functions

A probabilistic evolutionary optimization approach to compute quasiparticle braids

Topological quantum computing is an alternative framework for avoiding the quantum decoherence problem in quantum computation. The problem of executing a gate in this framework can be posed as the problem of braiding quasiparticles. Because these are not Abelian, the problem can be reduced to finding an optimal product of braid generators where the optimality is defined in terms of the gate approximation and the braid's length. In this paper we propose the use of different variants of estimation of distribution algorithms to deal with the problem. Furthermore, we investigate how the regularities of the braid optimization problem can be translated into statistical regularities by means of the Boltzmann distribution. We show that our best algorithm is able to produce many solutions that approximates the target gate with an accuracy in the order of $10^{-6}$, and have lengths up to 9 times shorter than those expected from braids of the same accuracy obtained with other methods.Comment: 9 pages,7 figures. Accepted at SEAL 201

Level-Based Analysis of the Population-Based Incremental Learning Algorithm

The Population-Based Incremental Learning (PBIL) algorithm uses a convex combination of the current model and the empirical model to construct the next model, which is then sampled to generate offspring. The Univariate Marginal Distribution Algorithm (UMDA) is a special case of the PBIL, where the current model is ignored. Dang and Lehre (GECCO 2015) showed that UMDA can optimise LeadingOnes efficiently. The question still remained open if the PBIL performs equally well. Here, by applying the level-based theorem in addition to Dvoretzky--Kiefer--Wolfowitz inequality, we show that the PBIL optimises function LeadingOnes in expected time $\mathcal{O}(n\lambda \log \lambda + n^2)$ for a population size $\lambda = \Omega(\log n)$, which matches the bound of the UMDA. Finally, we show that the result carries over to BinVal, giving the fist runtime result for the PBIL on the BinVal problem.Comment: To appea

From Understanding Genetic Drift to a Smart-Restart Parameter-less Compact Genetic Algorithm

One of the key difficulties in using estimation-of-distribution algorithms is choosing the population size(s) appropriately: Too small values lead to genetic drift, which can cause enormous difficulties. In the regime with no genetic drift, however, often the runtime is roughly proportional to the population size, which renders large population sizes inefficient. Based on a recent quantitative analysis which population sizes lead to genetic drift, we propose a parameter-less version of the compact genetic algorithm that automatically finds a suitable population size without spending too much time in situations unfavorable due to genetic drift. We prove a mathematical runtime guarantee for this algorithm and conduct an extensive experimental analysis on four classic benchmark problems both without and with additive centered Gaussian posterior noise. The former shows that under a natural assumption, our algorithm has a performance very similar to the one obtainable from the best problem-specific population size. The latter confirms that missing the right population size in the original cGA can be detrimental and that previous theory-based suggestions for the population size can be far away from the right values; it also shows that our algorithm as well as a previously proposed parameter-less variant of the cGA based on parallel runs avoid such pitfalls. Comparing the two parameter-less approaches, ours profits from its ability to abort runs which are likely to be stuck in a genetic drift situation.Comment: 4 figures. Extended version of a paper appearing at GECCO 202

Charakterisierung der mitochondrialen TIM22-Translokase des Menschen

Die TIM22-Translokase in der mitochondrialen Innenmembran vermittelt die Insertion von polytopen Innenmembranproteinen mit internen Signalsequenzen wie der mitochondrialen Metabolit-Carrier. Dabei unterstützt eine Gruppe von strukturell verwandten Proteinen mit charakteristischem Metallbindungsmotiv (Cys4-Motiv) die Passage der hydrophoben Vorstufenproteine über den Intermembranraum. Dies sind in der Hefe Tim9, Tim10 und Tim12 sowie Tim8 und Tim13. Die Familie dieser kleinen Tim-Proteine ist evolutionär konserviert. Im Menschen wurden sechs Mitglieder dieser Proteinfamilie identifiziert: Tim9, Tim10a und Tim10b sowie DDP1, DDP2 und Tim13. Im Rahmen dieser Arbeit wurden die Komponenten der TIM22-Translokase der Säugetiere strukturell und funktionell charakterisiert. Bei ihnen handelt es sich ebenfalls um mitochondriale Intermembranraumproteine. Sie sind in der Lage, mittels der vier konservierten Cysteinreste ein Zn2+-Ion zu binden und damit vermutlich eine Zinkfinger-Struktur auszubilden. Mutationen, die zu einem Verlust des DDP1 Proteins führen, sind die Ursache für das Mohr-Tranebjaerg Syndrom, einer neurodegenerativen Erkrankung, die sich im Wesentlichen durch Taubheit und Dystonie auszeichnet. Eine Punktmutation im DDP1-Gen, die zu einem Austausch eines der konservierten Cysteine führt (DDP1C66W), verursacht den Verlust der Zinkbindungskapazität und resultiert in einem fehlgefalteten, instabilen Protein. Es wurde gezeigt, dass das mutierte DDP1 nicht mehr in der Lage ist, mit seinem Partnerprotein Tim13 zu interagieren und keinen funktionellen DDP1-Tim13 Komplex ausbilden kann. Die menschlichen Proteine der Tim9 und Tim10-Gruppen, Tim9, Tim10a und Tim10b sind wie ihre homologen Hefeproteine in zwei hetero-oligomeren Komplexen organisiert, einem 70 kDa-Komplex bestehend aus Tim9 und Tim10a sowie einem 450 kDa Tim9-10a-10b-Komplex. Beide Komplexe sind fest mit der Innenmembran assoziiert. Tim10b zeigt eine geringere Sequenzhomologie zu Hefe-Tim10 als Tim10a. Es liegt genauso wie Tim12 nur in dem hochmolekularen Komplex vor und weist die stärkste Membranassoziation auf. Es zeigt damit strukturelle Ähnlichkeit zu Tim12. Aufgrund der Membranassoziation der kleinen TIM-Komplexe entfällt aber wahrscheinlich die Funktion des Tim12 als Vermittler zwischen dem löslichen Komplex und der Membran. Tim9, Tim10a und Tim10b sind wie die Hefe-Proteine am Import von mitochondrialen Carriern beteiligt. Die Bindung an Translokationsintermediate von Carrier-Vorstufenproteinen erfolgt in Abhängigkeit von zweiwertigen Kationen wie Zn2+. Die Struktur des TIM22-Komplexes weist signifikante Unterschiede zu der aus der Hefe bekannten Organisation auf. Humanes Tim22 ist im Vergleich zu Hefe-Tim22 wenig konserviert. Es liegt kein stabiler Komplex vor, der Tim22 und die kleinen Tim-Proteine enthält. Sie befinden sich vermutlich in dynamischer Interaktion mit Tim22, die wahrscheinlich nur während der Translokation eines Vorstufenproteins auftritt. Bisher ist kein Komplexpartner des humanen Tim22 bekannt. Homologe zu Tim54 und Tim18, den membranintegralen Komplexpartnern des Tim22, wurden in menschlichen Datenbanken nicht identifiziert. Aufgrund der veränderten strukturellen Organisation ist das menschliche Tim22 nicht in der Lage, mit den Proteinen aus der Hefe funktionell zu kooperieren. Es hat vermutlich eine Anpassung an veränderte Substratspezifizitäten stattgefunden, die auch die Beteiligung weiterer bisher unidentifizierter Komponenten der TIM22-Translokase einschließen könnte. Ein neues Intermembranraumprotein menschlicher Mitochondrien, Cmi1, ist an der Biogenese der kleinen Tim-Proteine beteiligt. Eine Überexpression im Hefesystem führt zur signifikanten Erhöhung der Proteinmengen von kleinen Tim-Proteinen im mitochondrialen Intermembranraum. Cmi1 unterstützt vermutlich die rasche stabile Faltung der neu importierten kleinen Tim-Proteine. Da Cmi1 in der Lage ist, Metall-Ionen zu binden vermittelt es möglicherweise den Transfer von Zink-Ionen

Strongly enhanced and tunable photovoltaic effect in ferroelectric-paraelectric superlattices

Ever since the first observation of a photovoltaic effect in ferroelectric BaTiO3, studies have been devoted to analyze this effect, but only a few attempted to engineer an enhancement. In conjunction, the steep progress in thin-film fabrication has opened up a plethora of previously unexplored avenues to tune and enhance material properties via growth in the form of superlattices. In this work, we present a strategy wherein sandwiching a ferroelectric BaTiO3 in between paraelectric SrTiO3 and CaTiO3 in a superlattice form results in a strong and tunable enhancement in photocurrent. Comparison with BaTiO3 of similar thickness shows the photocurrent in the superlattice is 103 times higher, despite a nearly two-thirds reduction in the volume of BaTiO3. The enhancement can be tuned by the periodicity of the superlattice, and persists under 1.5 AM irradiation. Systematic investigations highlight the critical role of large dielectric permittivity and lowered bandgap

Replica Symmetry Breaking in the Random Replicant Model

We study the statistical mechanics of a model describing the coevolution of species interacting in a random way. We find that at high competition replica symmetry is broken. We solve the model in the approximation of one step replica symmetry breaking and we compare our findings with accurate numerical simulations.Comment: 12 pages, TeX, 5 postscript figures are avalaible upon request, submitted to Journal of Physics A: Mathematical and Genera

Explicit memory schemes for evolutionary algorithms in dynamic environments

Copyright @ 2007 Springer-VerlagProblem optimization in dynamic environments has atrracted a growing interest from the evolutionary computation community in reccent years due to its importance in real world optimization problems. Several approaches have been developed to enhance the performance of evolutionary algorithms for dynamic optimization problems, of which the memory scheme is a major one. This chapter investigates the application of explicit memory schemes for evolutionary algorithms in dynamic environments. Two kinds of explicit memory schemes: direct memory and associative memory, are studied within two classes of evolutionary algorithms: genetic algorithms and univariate marginal distribution algorithms for dynamic optimization problems. Based on a series of systematically constructed dynamic test environments, experiments are carried out to investigate these explicit memory schemes and the performance of direct and associative memory schemes are campared and analysed. The experimental results show the efficiency of the memory schemes for evolutionary algorithms in dynamic environments, especially when the environment changes cyclically. The experimental results also indicate that the effect of the memory schemes depends not only on the dynamic problems and dynamic environments but also on the evolutionary algorithm used