Genetic algorithms with DNN-based trainable crossover as an example of partial specialization of general search

Universal induction relies on some general search procedure that is doomed to be inefficient. One possibility to achieve both generality and efficiency is to specialize this procedure w.r.t. any given narrow task. However, complete specialization that implies direct mapping from the task parameters to solutions (discriminative models) without search is not always possible. In this paper, partial specialization of general search is considered in the form of genetic algorithms (GAs) with a specialized crossover operator. We perform a feasibility study of this idea implementing such an operator in the form of a deep feedforward neural network. GAs with trainable crossover operators are compared with the result of complete specialization, which is also represented as a deep neural network. Experimental results show that specialized GAs can be more efficient than both general GAs and discriminative models.Comment: AGI 2017 procedding, The final publication is available at link.springer.co

Gas burners used for combustion of biomass-generated gas and gas-like waste

Original burners used for ecologically safe combustion of natural (soil) gas implement stadial combustion with varying levels of oxygen deficiency in their separate zones created by the flame vortex, which correlates with the capabilities of other effective hardware. Process of NOx reduction with the use of uncomplete combustion products is organized simultaneously with the use of the new technology of maintaining inner ejection in the flame vortex and zone of intensive mixing while weakening the whole flame vortex's twist. This lets us adapt the designs for combustion of biomass-generated gas and gas-like waste. © 2018 IOP Publishing Ltd

dimer paramagnetic centers in lead germanate crystals doped with iron and halogen (Cl-, Br-, F-) ions

The dimer complexes Fe3+-Cl-, Fe3+-Br-, and Fe3+-O2- in ferroelectric lead germanate crystals doped with iron and annealed in chlorine-, bromine-, and fluorine-containing atmospheres have been studied using the electron paramagnetic resonance method. These complexes are formed by Fe3+ ions in the trigonal position of lead and their associated anions located in the interstitial channel of the structure. The positions of the charge-compensating anions in the channel have been discussed based on the analysis of the parameters of the spin Hamiltonian and their temperature dependence. © 2013 Pleiades Publishing, Ltd

Electron paramagnetic resonance of Gd3+ ions in Ca1-x-yYxGdyF2+x+y crystals

Electron paramagnetic resonance of Ca1-x-yYxGdyF2+x+y single crystals has revealed spectra that are not typical of gadolinium-doped CaF2 crystals. These spectra have a nearly tetragonal symmetry and are most probably caused by Gd3+ ions localized in yttrium clusters. Weak spectra of tetragonal Gd3+ centers, whose parameters are close to those of a cubic gadolinium center caused by an isolated Gd3+ ion, have been also detected. These centers are attributed to isolated Gd3+ ions localized near octahedral rare-earth clusters or their associations. © 2013 Pleiades Publishing, Ltd

Changes of the body functions during long-term hypokinesia

Prolonged hypokinesis (100-170 days) studied in 2000 rats kept in cages limiting their mobility provoked considerable changes in the gaseous and energetic metabolism: an elevation of the total gaseous metabolism and of the rate of O2 requirement by the muscles (in the late periods of hypokinesis) and a change in the intensity of tissue respiration of the liver and myocardium. There also proved to be a reduction in the level of phosphorylation and separation of oxidative phosphorylation in the myocardium, liver, and partially in the skeletal muscle. Prolonged hypokinesia led to changes in tissue metabolism: a disturbance of development of the animals, a marked delay and an increase in the weight of the organism and the muscular system, and disturbances of the mineral and protein metabolism. Prolonged hypokinesis also lead to exhaustion of the hypothalamus-hypophysis-adrenal cortex system

Specific features of the electron paramagnetic resonance spectrum in the vicinity of the convergence of the transitions of gadolinium centers in Pb5(Ge1 - xSix)3O11

An anomalous electron paramagnetic resonance spectrum of the transitions -1/2 ↔ +1/2 of four Gd3+-Si dimer clusters in the Pb5(Ge1 - xSix)3O11 crystals doped with gadolinium has been found in the vicinity of the orientation of the magnetic field along the optic axis of the crystal. It has been assumed that this spectrum is caused by rapid transitions between the spin packets of the initial resonances due to the crossrelaxation. A computer simulation of the spectrum has been carried out. The results obtained adequately describe the experiment. © 2013 Pleiades Publishing, Ltd

Unsupervised Video Summarization via Attention-Driven Adversarial Learning

This paper presents a new video summarization approach that integrates an attention mechanism to identify the signi cant parts of the video, and is trained unsupervisingly via generative adversarial learning. Starting from the SUM-GAN model, we rst develop an improved version of it (called SUM-GAN-sl) that has a signi cantly reduced number of learned parameters, performs incremental training of the model's components, and applies a stepwise label-based strategy for updating the adversarial part. Subsequently, we introduce an attention mechanism to SUM-GAN-sl in two ways: i) by integrating an attention layer within the variational auto-encoder (VAE) of the architecture (SUM-GAN-VAAE), and ii) by replacing the VAE with a deterministic attention auto-encoder (SUM-GAN-AAE). Experimental evaluation on two datasets (SumMe and TVSum) documents the contribution of the attention auto-encoder to faster and more stable training of the model, resulting in a signi cant performance improvement with respect to the original model and demonstrating the competitiveness of the proposed SUM-GAN-AAE against the state of the art

Programming languages and artificial general intelligence

Despite the fact that there are thousands of programming languages existing there is a huge controversy about what language is better to solve a particular problem. In this paper we discuss requirements for programming language with respect to AGI research. In this article new language will be presented. Unconventional features (e.g. probabilistic programming and partial evaluation) are discussed as important parts of language design and implementation. Besides, we consider possible applications to particular problems related to AGI. Language interpreter for Lisp-like probabilistic mixed paradigm programming language is implemented in Haskell