Evolving robots able to self-localize in the environment: the importance of viewing cognition as the result of processes occurring at different time-scales

In this paper we address the problem of synthesizing mobile robots able to solve problems in which they cannot merely react to sensory input, but have to maintain an internal state as well. More precisely, we shall show how autonomous robots synthesized through an evolutionary process can solve problems that necessarily require an ability to integrate sensorimotor information over time. By presenting the result of a set of experiments in which evolving robots are asked to navigate and self-localize in the environment, we shall show that successful results can be achieved by providing evolving individuals with neural controllers with neurons that: (a) vary their activity at different rates to detect regularities at different time-scales in the sensorimotor flow; and (b) use thresholded activation functions to detect events extending over time.     

A lagrangian propagator for artificial neural networks in constraint programming

This paper discusses a new method to perform propagation over a (two-layer, feed-forward) Neural Network embedded in a Constraint Programming model. The method is meant to be employed in Empirical Model Learning, a technique designed to enable optimal decision making over systems that cannot be modeled via conventional declarative means. The key step in Empirical Model Learning is to embed a Machine Learning model into a combinatorial model. It has been showed that Neural Networks can be embedded in a Constraint Programming model by simply encoding each neuron as a global constraint, which is then propagated individually. Unfortunately, this decomposition approach may lead to weak bounds. To overcome such limitation, we propose a new network-level propagator based on a non-linear Lagrangian relaxation that is solved with a subgradient algorithm. The method proved capable of dramatically reducing the search tree size on a thermal-aware dispatching problem on multicore CPUs. The overhead for optimizing the Lagrangian multipliers is kept within a reasonable level via a few simple techniques. This paper is an extended version of [27], featuring an improved structure, a new filtering technique for the network inputs, a set of overhead reduction techniques, and a thorough experimentation.     

Robust linear parameter‐varying control of induction motors

The paper deals with the motion control of an induction motor. Because the nonlinear state equations describing the dynamics of such a machine can be embedded into a linear model with the rotor speed ω as a varying parameter, advantage is taken of some recent results on the control of linear parameter‐varying systems, thus ensuring stability independently of how the varying parameter changes in time within a compact set. The adopted control structure consists of a fast inner electric loop that controls the stator currents and an outer mechanical loop that generates the torque acting on the motor shaft. Of crucial importance is the design of the internal model controller for the current loop. In particular, it is proved that an algebraically equivalent electric motor model admits a Lyapunov function that, together with its Lyapunov derivative, is independent of ω and of all motor parameters. This result allows us to find an upper bound on the norm of the Youla–Kucera parameter that ensures robust stability against speed measurement errors. Simulations carried out on a benchmark motor model show that the adopted control strategy performs well. Copyright © 2014 John Wiley & Sons, Ltd.     

Groundwater use in Spain: an overview in light of the EU Water Framework Directive

In semi-arid regions, aquifers provide a series of practical advantages that make them preferential sources of water supply. In Spain, groundwater meets about one-fifth of the total water demand and is used to irrigate over one-third of the total irrigated land. This article examines groundwater use in Spain from the perspective of the EU Water Framework Directive. Analysis of different sector uses suggests that core problems (and solutions) related to groundwater lie in agricultural uses and that the Directive's environmental requirements remain distant from reality on the ground, where economic, political and social reasons prevail on legal obligations set by national and supranational authorities.     

A flexible FPGA implementation for illuminance–reflectance video enhancement

Digital cameras, new generation phones, commercial TV sets and, in general, all modern devices for image acquisition and visualization can benefit from algorithms for image enhancement suitable to work in real time and preferably with limited power consumption. Among the various methods described in the scientific literature, Retinex-based approaches are able to provide very good performances, but unfortunately they typically require a high computational effort. In this article, we propose a flexible and effective architecture for the real-time enhancement of video frames, suitable to be implemented in a single FPGA device. The video enhancement algorithm is based on a modified version of the Retinex approach. This method, developed to control the dynamic range of poorly illuminated images while preserving the visual details, has been improved by the adoption of a new model to perform illuminance estimation. The video enhancement parameters are controlled in real time through an embedded microprocessor which makes the system able to modify its behavior according to the characteristics of the input images, and using information about the surrounding light conditions.     

Experiences with large-scale operational trials of ALTO-enhanced P2P filesharing in an intra-ISP scenario

Application Layer Traffic Optimization (ALTO) has recently gained attention in the research and standardisation community as a way for a network operator to guide the peer selection process of distributed applications by providing network layer topology information. In particular P2P applications are expected to gain from ALTO, due to the many connections peers form among each other, often without taking network layer topology information into account. In this paper, we present results of an extensive intra-ISP trial with an ALTO-enhanced P2P filesharing software. In summary, our results show that—depending on the concrete setting and on the distribution of upload capacity in the network—ALTO enables an ISP to save operational costs significantly while not degrading application layer performance noticeably. In addition, based on our experience we are able to give advice to operators on how to save costs with ALTO while not sacrificing application layer performance at all.