Sustainable Cooperative Coevolution with a Multi-Armed Bandit

This paper proposes a self-adaptation mechanism to manage the resources allocated to the different species comprising a cooperative coevolutionary algorithm. The proposed approach relies on a dynamic extension to the well-known multi-armed bandit framework. At each iteration, the dynamic multi-armed bandit makes a decision on which species to evolve for a generation, using the history of progress made by the different species to guide the decisions. We show experimentally, on a benchmark and a real-world problem, that evolving the different populations at different paces allows not only to identify solutions more rapidly, but also improves the capacity of cooperative coevolution to solve more complex problems.Comment: Accepted at GECCO 201

Fast, Accurate and Object Boundary-Aware Surface Normal Estimation from Depth Maps

This paper proposes a fast and accurate surface normal estimation method which can be directly used on depth maps (organized point clouds). The surface normal estimation process is formulated as a closed-form expression. In order to reduce the effect of measurement noise, the averaging operation is utilized in multi-direction manner. The multi-direction normal estimation process is reformulated in the next step to be implemented efficiently. Finally, a simple yet effective method is proposed to remove erroneous normal estimation at depth discontinuities. The proposed method is compared to well-known surface normal estimation algorithms. The results show that the proposed algorithm not only outperforms the baseline algorithms in term of accuracy, but also is fast enough to be used in real-time applications

Quantification of the morphology of gold grains in 3D using X-ray microscopy and SEM photogrammetry

The shape of gold is widely used in mineral exploration and in sedimentology to estimate the distance of transport from the source to the site of deposition. However, estimation of the morphology is based on qualitative observations or on the quantification of shape in 2D. The 3D analysis of grain shape is useful for accurate morphometric quantification and to evaluate its volume, which is related to particle size. This study compares X-ray 3D microscope and 3D SEM photogrammetry to reconstruct the shape of gold particles. These new methods are exploited to quantify the shape of gold grains 85 to 300 μm in size. The shape parameters, such as axial lengths, surface area, volume, diameter of curvature of all corners, and diameter of the largest inscribed sphere and smallest circumscribed sphere are measured on a particle in order to estimate shape factors such as flatness ratios, shape indices, sphericity, and roundness. Most shape parameters and shape factors estimated on the same gold grain with simple geometry are similar between the two approaches. This result validates these methods for the 3D description of gold particles with simple morphology, while providing a methodology for describing grains with more complex geometry

Multi-method 2D and 3D reconstruction of gold grains morphology in alluvial deposits : a review and application to the Rivière du Moulin (Québec, Canada)

The aim of this paper is to document and compare the 2D qualitative and semi-quantitative methods currently used to describe the shape of gold grains in fluvial environments with the 3D quantitative methods using X-ray microtomography and SEM photogrammetry. These 3D methods are used to compute flatness, roundness, convexity, sphericity and ellipticity shape descriptors of 13 gold grains from the Rivière du Moulin (Québec, Canada) in order to quantify the morphological change along 9 km of fluvial transport. Gold grains have moderate to high values of flatness, compactness, sphericity and ellipticity indices that do not change significantly with distance of transport, whereas the roundness increases during transport. Gold grains are used to compare 2D and 3D methods, and the results show small differences (<8%) when shape descriptors are computed using image analysis software, whereas the difference (up to 70%) is more important for 2D measurements performed by a human operator. For application and characterization on a large set of gold grains, the 2D methods offer the advantage of speed, whereas, for a more detailed study on a limited number of gold grains, 3D methods enable estimation of the volume and yield more detailed shape descriptor changes during fluvial transport

Optimizing Low-Discrepancy Sequences with an Evolutionary Algorithm

International audienceMany elds rely on some stochastic sampling of a given com- plex space. Low-discrepancy sequences are methods aim- ing at producing samples with better space-lling properties than uniformly distributed random numbers, hence allow- ing a more ecient sampling of that space. State-of-the-art methods like nearly orthogonal Latin hypercubes and scram- bled Halton sequences are congured by permutations of in- ternal parameters, where permutations are commonly done randomly. This paper proposes the use of evolutionary al- gorithms to evolve these permutations, in order to optimize a discrepancy measure. Results show that an evolution- ary method is able to generate low-discrepancy sequences of signicantly better space-lling properties compared to sequences congured with purely random permutations

Multiple Exposition to a Driving Simulator Reduces Simulator Symptoms for Elderly Drivers

This study examines how older drivers responded to repeated exposures to a driver simulator. Older active and fit drivers participated in 5 simulator sessions within a 14-day period. For each session, simulator sickness symptoms were measured with the Simulator Sickness Questionnaire at baseline and post-session. In addition, participants completed a 10-cm visual analog scale (0= no symptom, 10= mild nausea) at baseline and after a familiarization scenario and post-session. Overall, older adults adapted to the driving simulator and by the fourth session, they showed no difference in sickness scores between the baseline and the post-session measurements. Increasing the exposure duration at session 5 yielded an increase in the sickness symptoms. These results suggest that shorterduration multiple exposures could reduce simulator sickness symptoms in elderly drivers and allow a more effective use of simulators for training by preventing early withdrawal of participants

Multiple-Session Simulator Training for Older Drivers and On-Road Transfer of Learning

Driving retraining classes may offer an opportunity to attenuate some of the aging manifestation that may alter driving skills. Unfortunately, there are suggestions that classroom programs do not allow to improve the driving performance of elderly drivers. The aim of this study was to evaluate if specific simulator training sessions with video-based feedback can modify on-road behaviors of elderly drivers. In order to evaluate the effectiveness of the training, 10 elderly drivers who received feedback were tested before and after the training program with an on-road standardized evaluation. A control group (12 older drivers) also participated. Participants in this group received a classroom training program and similar exposure to driving in a simulator but without drivingspecific feedback. After attending the training program, the control group showed no modification of their driving performance (on-road score, frequency of successful turning maneuvers and frequency blind spot verification before lane change maneuvers). On the other hand, participants in the feedback group improved their driving skills for all maneuvers that were evaluated. These results suggest that simulator training transferred effectively to on-road performance. In order to be effective, driving programs should include active practice sessions with driving specific feedback