Search results for "simulation"
showing 10 items of 5095 documents
Using Inverse Reinforcement Learning with Real Trajectories to Get More Trustworthy Pedestrian Simulations
2020
Reinforcement learning is one of the most promising machine learning techniques to get intelligent behaviors for embodied agents in simulations. The output of the classic Temporal Difference family of Reinforcement Learning algorithms adopts the form of a value function expressed as a numeric table or a function approximator. The learned behavior is then derived using a greedy policy with respect to this value function. Nevertheless, sometimes the learned policy does not meet expectations, and the task of authoring is difficult and unsafe because the modification of one value or parameter in the learned value function has unpredictable consequences in the space of the policies it represents…
A model for torque losses in variable displacement axial piston motors
2018
This paper includes a comparison of earlier presented models for torque losses in hydraulic motors and several proposed models that all rely on data typically available for a system engineer. The new models and the old ones are compared. The new models are all based on a model developed by Jeong 2007 with an expansion that include variable displacement. All of the new models yield very good accuracy down to approximately 50% of maximum displacement and down to approximately 15% of maximum speed. In these operational ranges the deviation in torque is less than 1%. The main purpose of the new models is to facilitate simulations of hydraulically actuated winches with a balance between accuracy…
Onset of cohesion in cement paste
2004
It is generally agreed that the cohesion of cement paste occurs through the formation of a network of nanoparticles of a calcium-silicate-hydrate ("C-S-H"). However, the mechanism by which these particles develop this cohesion has not been established. Here we propose a dielectric continuum model which includes all ionic interactions within a dispersion of C-S-H particles. It takes into account all co-ions and counterions explicitly (with pure Coulomb interactions between ions and between ions and the surfaces) and makes no further assumptions concerning their hydration or their interactions with the surface sites. At high surface charge densities, the model shows that the surface charge of…
A note on best proximity point theory using proximal contractions
2018
In this paper, a reduction technique is used to show that some recent results on the existence of best proximity points for various classes of proximal contractions can be concluded from the corresponding results in fixed point theory.
Stabilized branch-and-price algorithms for vector packing problems
2018
Abstract This paper considers packing and cutting problems in which a packing/cutting pattern is constrained independently in two or more dimensions. Examples are restrictions with respect to weight, length, and value. We present branch-and-price algorithms to solve these vector packing problems (VPPs) exactly. The underlying column-generation procedure uses an extended master program that is stabilized by (deep) dual-optimal inequalities. While some inequalities are added to the master program right from the beginning (static version), other violated dual-optimal inequalities are added dynamically. The column-generation subproblem is a multidimensional knapsack problem, either binary, boun…
The minimum mean cycle-canceling algorithm for linear programs
2022
Abstract This paper presents the properties of the minimum mean cycle-canceling algorithm for solving linear programming models. Originally designed for solving network flow problems for which it runs in strongly polynomial time, most of its properties are preserved. This is at the price of adapting the fundamental decomposition theorem of a network flow solution together with various definitions: that of a cycle and the way to calculate its cost, the residual problem, and the improvement factor at the end of a phase. We also use the primal and dual necessary and sufficient optimality conditions stated on the residual problem for establishing the pricing step giving its name to the algorith…
Best proximity point theorems for proximal cyclic contractions
2017
The purpose of this article is to compute a global minimizer of the function $$x\longrightarrow d(x, Tx)$$ , where T is a proximal cyclic contraction in the framework of a best proximally complete space, thereby ensuring the existence of an optimal approximate solution, called a best proximity point, to the equation $$Tx=x$$ when T is not necessarily a self-mapping.
Combined column-and-row-generation for the optimal communication spanning tree problem
2018
Abstract This paper considers the exact solution of the optimal communication spanning tree problem (OCSTP), which can be described as follows: Given an undirected graph with transportation costs on every edge and communication requirements for all pairs of vertices, the OCSTP seeks for a spanning tree that minimizes the sum of the communication costs between all pairs of vertices, where the communication cost of a pair of vertices is defined as their communication requirement multiplied by the transportation cost of the unique tree path that connects the two vertices. Two types of compact formulations for OCSTP were presented in the literature. The first one is a four-index model based on …
Ensuring the Reliability of an Autonomous Vehicle
2017
International audience; In automotive applications, several components, offering different services, can be composed in order to handle one specific task (autonomous driving for example). Nevertheless, component composition is not straightforward and is subject to the occurrence ofbugs resulting from components or services incompatibilities for instance. Hence, bugs detection in component-based systems at thedesign level is very important, particularly, when the developed system concerns automotive applications supporting critical services.In this paper, we propose a formal approach for modeling and verifying the reliability of an autonomous vehicle system, communicatingcontinuously with of…
Understanding the Importance of Proper Incentives for Critical Infrastructures Management – How System Dynamics Can Help
2016
International audience; Computer and information systems are now at the core of numerous critical infrastructures. However, their security management is by far not a trivial issue. Further, these systems, by their very nature, belong to the domain of complex systems, where system dynamics (SD) is an established method, which aims at modelling such systems, their analysis and understanding. Further, on this basis it enables simulation of various policies to properly manage complex systems. More precisely, through understanding of the basic elements of the whole mosaic and their interplay, proper incentives can be tested. And this is important, because proper incentives can lead to the desire…