Analysis of the (μ/μI,λ)(\mu/\mu_I,\lambda)-CSA-ES with Repair by Projection Applied to a Conically Constrained Problem

Theoretical analyses of evolution strategies are indispensable for gaining a deep understanding of their inner workings. For constrained problems, rather simple problems are of interest in the current research. This work presents a theoretical analysis of a multi-recombinative evolution strategy with cumulative step size adaptation applied to a conically constrained linear optimization problem. The state of the strategy is modeled by random variables and a stochastic iterative mapping is introduced. For the analytical treatment, fluctuations are neglected and the mean value iterative system is considered. Non-linear difference equations are derived based on one-generation progress rates. Based on that, expressions for the steady state of the mean value iterative system are derived. By comparison with real algorithm runs, it is shown that for the considered assumptions, the theoretical derivations are able to predict the dynamics and the steady state values of the real runs.Comment: This is a PREPRINT of an article that has been accepted for publication in the journal MIT Press Evolutionary Computation (ECJ). 25 pages + supplementary material. The work was supported by the Austrian Science Fund FWF under grant P29651-N3

BiERL: A Meta Evolutionary Reinforcement Learning Framework via Bilevel Optimization

Evolutionary reinforcement learning (ERL) algorithms recently raise attention in tackling complex reinforcement learning (RL) problems due to high parallelism, while they are prone to insufficient exploration or model collapse without carefully tuning hyperparameters (aka meta-parameters). In the paper, we propose a general meta ERL framework via bilevel optimization (BiERL) to jointly update hyperparameters in parallel to training the ERL model within a single agent, which relieves the need for prior domain knowledge or costly optimization procedure before model deployment. We design an elegant meta-level architecture that embeds the inner-level's evolving experience into an informative population representation and introduce a simple and feasible evaluation of the meta-level fitness function to facilitate learning efficiency. We perform extensive experiments in MuJoCo and Box2D tasks to verify that as a general framework, BiERL outperforms various baselines and consistently improves the learning performance for a diversity of ERL algorithms.Comment: Published as a conference paper at European Conference on Artificial Intelligence (ECAI) 202

The microwave emissivity variability of snow covered first-year sea ice from late winter to early summer: a model study

Satellite observations of microwave brightness temperatures between 19 GHz and 85 GHz are the main data sources for operational sea-ice monitoring and retrieval of ice concentrations. However, microwave brightness temperatures depend on the emissivity of snow and ice, which is subject to pronounced seasonal variations and shows significant hemispheric contrasts. These mainly arise from differences in the rate and strength of snow metamorphism and melt. We here use the thermodynamic snow model SNTHERM forced by European Re-Analysis (ERA) interim data and the Microwave Emission Model of Layered Snowpacks (MEMLS), to calculate the sea-ice surface emissivity and to identify the contribution of regional patterns in atmospheric conditions to its variability in the Arctic and Antarctic. The computed emissivities reveal a pronounced seasonal cycle with large regional variability. The emissivity variability increases from winter to early summer and is more pronounced in the Antarctic. In the pre-melt period (January–May, July–November) the standard deviations in surface microwave emissivity due to diurnal, regional and inter-annual variability of atmospheric forcing reach up to Δε = 0.034, 0.043, and 0.097 for 19 GHz, 37 GHz and 85 GHz channels, respectively. Between 2000 and 2009, small but significant positive emissivity trends were observed in the Weddell Sea during November and December as well as in Fram Strait during February, potentially related to earlier melt onset in these regions. The obtained results contribute to a better understanding of the uncertainty and variability of sea-ice concentration and snow-depth retrievals in regions of high sea-ice concentrations

The uses of coherent structure (Dryden Lecture)

The concept of coherent structure in turbulent flow is a revolutionary idea which is being developed by evolutionary means. The main objective of this review is to list some solid achievements, showing what can be done by using the concept of coherent structure that cannot be done without it. The nature of structure is described in terms of some related concepts, including celerity, topology, and the phenomenon of coalescence and splitting of structure. The main emphasis is on the mixing layer, as the one flow whose structure is well enough understood so that technical applications are now being made in problems of mixing and chemistry. An attempt is made to identify some conceptual and experimental obstacles that stand in the way of progress in other technically important flows, particularly the turbulent boundary layer. A few comments are included about the role of structure in numerical simulations and in current work on manipulation and control of turbulent flow. Some recent developments are cited which suggest that the time is nearly right for corresponding advances to occur in turbulence modeling

End-to-end kilonova models of neutron-star mergers with delayed black-hole formation

We investigate the nucleosynthesis and kilonova properties of binary neutron-star (NS) merger models which lead to intermediate remnant lifetimes of ~0.1-1seconds until black-hole (BH) formation and describe all components of material ejected during the dynamical merger phase, NS-remnant evolution, and final viscous disintegration of the BH torus after gravitational collapse. To this end we employ a combination of hydrodynamics, nucleosynthesis, and radiative-transfer tools to achieve a consistent end-to-end modeling of the system and its observables. We adopt a novel version of the Shakura-Sunyaev scheme allowing to vary the approximate turbulent viscosity inside the NS remnant independently of the surrounding disk. We find that asymmetric progenitors lead to shorter remnant lifetimes and enhanced ejecta masses, although the viscosity affects the absolute values of these characteristics. The integrated production of lanthanides and heavier elements in such binary systems is sub-solar, suggesting that the considered scenarios contribute in a sub-dominant fashion to r-process enrichment. One reason is that BH-tori formed after delayed collapse exhibit less neutron-rich conditions than typically found, and often assumed in previous BH-torus models, for early BH formation. The outflows in our models feature strong anisotropy as a result of the lanthanide-poor polar neutrino-driven wind pushing aside lanthanide-rich dynamical ejecta. Considering the complexity of the models, the estimated kilonova light curves show promising agreement with AT2017gfo after times of several days, while the remaining inconsistencies at early times could possibly be overcome in binary configurations with a more dominant neutrino-driven wind relative to the dynamical ejecta.Comment: 16 pages, 9 figures, 1 table, accepted to ApJ

Probabilistic multiple kernel learning

The integration of multiple and possibly heterogeneous information sources for an overall decision-making process has been an open and unresolved research direction in computing science since its very beginning. This thesis attempts to address parts of that direction by proposing probabilistic data integration algorithms for multiclass decisions where an observation of interest is assigned to one of many categories based on a plurality of information channels

Geometry and dynamics in Gromov hyperbolic metric spaces: With an emphasis on non-proper settings

Our monograph presents the foundations of the theory of groups and semigroups acting isometrically on Gromov hyperbolic metric spaces. Our work unifies and extends a long list of results by many authors. We make it a point to avoid any assumption of properness/compactness, keeping in mind the motivating example of $\mathbb H^\infty$, the infinite-dimensional rank-one symmetric space of noncompact type over the reals. The monograph provides a number of examples of groups acting on $\mathbb H^\infty$ which exhibit a wide range of phenomena not to be found in the finite-dimensional theory. Such examples often demonstrate the optimality of our theorems. We introduce a modification of the Poincar\'e exponent, an invariant of a group which gives more information than the usual Poincar\'e exponent, which we then use to vastly generalize the Bishop--Jones theorem relating the Hausdorff dimension of the radial limit set to the Poincar\'e exponent of the underlying semigroup. We give some examples based on our results which illustrate the connection between Hausdorff dimension and various notions of discreteness which show up in non-proper settings. We construct Patterson--Sullivan measures for groups of divergence type without any compactness assumption. This is carried out by first constructing such measures on the Samuel--Smirnov compactification of the bordification of the underlying hyperbolic space, and then showing that the measures are supported on the bordification. We study quasiconformal measures of geometrically finite groups in terms of (a) doubling and (b) exact dimensionality. Our analysis characterizes exact dimensionality in terms of Diophantine approximation on the boundary. We demonstrate that some Patterson--Sullivan measures are neither doubling nor exact dimensional, and some are exact dimensional but not doubling, but all doubling measures are exact dimensional.Comment: A previous version of this document included Section 12.5 (Tukia's isomorphism theorem). The results of that subsection have been split off into a new document which is available at arXiv:1508.0696

Insights into Protein-Ligand Molecular Recognition: Thermodynamic, Kinetic and Structural Characterization of Inhibitor Binding to Aldose Reductase and Carbonic Anhydrase II

Two pathological relevant proteins, human aldose reductase and human carbonic anhydrase, were used as model proteins to get insights into the process of molecular recognition. The thermodynamics and kinetics of the formation process of protein ligand complex formation were studied