Neutrality: A Necessity for Self-Adaptation

Self-adaptation is used in all main paradigms of evolutionary computation to increase efficiency. We claim that the basis of self-adaptation is the use of neutrality. In the absence of external control neutrality allows a variation of the search distribution without the risk of fitness loss.Comment: 6 pages, 3 figures, LaTe

On Classes of Functions for which No Free Lunch Results Hold

In a recent paper it was shown that No Free Lunch results hold for any subset F of the set of all possible functions from a finite set X to a finite set Y iff F is closed under permutation of X. In this article, we prove that the number of those subsets can be neglected compared to the overall number of possible subsets. Further, we present some arguments why problem classes relevant in practice are not likely to be closed under permutation.Comment: 8 pages, 1 figure, see http://www.neuroinformatik.ruhr-uni-bochum.de

Trajectory-Based Off-Policy Deep Reinforcement Learning

Policy gradient methods are powerful reinforcement learning algorithms and have been demonstrated to solve many complex tasks. However, these methods are also data-inefficient, afflicted with high variance gradient estimates, and frequently get stuck in local optima. This work addresses these weaknesses by combining recent improvements in the reuse of off-policy data and exploration in parameter space with deterministic behavioral policies. The resulting objective is amenable to standard neural network optimization strategies like stochastic gradient descent or stochastic gradient Hamiltonian Monte Carlo. Incorporation of previous rollouts via importance sampling greatly improves data-efficiency, whilst stochastic optimization schemes facilitate the escape from local optima. We evaluate the proposed approach on a series of continuous control benchmark tasks. The results show that the proposed algorithm is able to successfully and reliably learn solutions using fewer system interactions than standard policy gradient methods.Comment: Includes appendix. Accepted for ICML 201

An Optimal Algorithm to Solve the Combined Task Allocation and Path Finding Problem

We consider multi-agent transport task problems where, e.g. in a factory setting, items have to be delivered from a given start to a goal pose while the delivering robots need to avoid collisions with each other on the floor. We introduce a Task Conflict-Based Search (TCBS) Algorithm to solve the combined delivery task allocation and multi-agent path planning problem optimally. The problem is known to be NP-hard and the optimal solver cannot scale. However, we introduce it as a baseline to evaluate the sub-optimality of other approaches. We show experimental results that compare our solver with different sub-optimal ones in terms of regret

How Does Climate Change Affect Endophytic Fungi?

Plant-associated microorganisms can have major effects on plant health, but climate change can affect plant microbiomes. While it is unknown how climate change will affect aboveground plant-associated microorganisms, such as foliar endophytic fungi, we hypothesize that increased CO2 concentrations will increase species richness and diversity in endophytic fungal communities, because increased plant photosynthesis under elevated CO2 will increase the resources available to the fungi

Analyse et comparaison de procédures d'optimisation en tomodensitométrie

La est une modalité d'imagerie médicale utilisée pour représenter la structure interne d'un être vivant. La reconstruction de cette image doit être rapide et stable. En outre, le résultat doit représenter le plus fidèlement que possible la réalité. Ce document propose de comparer les performances de quelques algorithmes itératifs en termes de qualité d'image reconstruite et de durée de calcul. Parmi les algorithmes testés, certains ont été développés spécialement pour le problème de tomodensitométrie alors que d'autres sont des solveurs généraux. De plus, chacun des algorithmes sera testé avec une variante incluant un terme de régularisation. Ce document propose de tester quelques variantes de gradient conjugué non-linéaire afin d'observer leur performance en tomodensitométrie

Age-related cellular copper dynamics in the fungal ageing model Podospora anserina and in ageing human fibroblasts

In previous investigations an impact of cellular copper homeostasis on ageing of the ascomycete Podospora anserina has been demonstrated. Here we provide new data indicating that mitochondria play a major role in this process. Determination of copper in the cytosolic fraction using total reflection X-ray fluorescence spectroscopy analysis and eGfp reporter gene studies indicate an age-related increase of cytosolic copper levels. We show that components of the mitochondrial matrix (i.e. eGFP targeted to mitochondria) become released from the organelle during ageing. Decreasing the accessibility of mitochondrial copper in P. anserina via targeting a copper metallothionein to the mitochondrial matrix was found to result in a switch from a copper-dependent cytochrome-c oxidase to a copper-independent alternative oxidase type of respiration and results in lifespan extension. In addition, we demonstrate that increased copper concentrations in the culture medium lead to the appearance of senescence biomarkers in human diploid fibroblasts (HDFs). Significantly, expression of copper-regulated genes is induced during in vitro ageing in medium devoid of excess copper suggesting that cytosolic copper levels also increase during senescence of HDFs. These data suggest that the identified molecular pathway of age-dependent copper dynamics may not be restricted to P. anserina but may be conserved from lower eukaryotes to humans