Cooperating with Unknown Teammates in Complex Domains: A Robot Soccer Case Study of Ad Hoc Teamwork

Integral equation–based numerical methods are directly applicable to homogeneous elliptic PDEs and offer the ability to solve these with high accuracy and speed on complex domains. In this paper, such a method is extended to the heat equation with inhomogeneous source terms. First, the heat equation is discretised in time, then in each time step we solve a sequence of so-called modified Helmholtz equations with a parameter depending on the time step size. The modified Helmholtz equation is then split into two: a homogeneous part solved with a boundary integral method and a particular part, where the solution is obtained by evaluating a volume potential over the inhomogeneous source term over a simple domain. In this work, we introduce two components which are critical for the success of this approach: a method to efficiently compute a high-regularity extension of a function outside the domain where it is defined, and a special quadrature method to accurately evaluate singular and nearly singular integrals in the integral formulation of the modified Helmholtz equation for all time step sizes.

A new method is described in this paper that has the potential to greatly extend the range of application of Eulerian computational methods for many problems. The new method has many of the advantages of Green's Function based integral equation methods for long distance propagation since the propagation distance can be indefinitely long. However, unlike Green's Function schemes, which are useful for uniform index of refraction in simple domains, since the new method is an Eulerian finite difference technique; it allows short pulses to automatically propagate through regions of varying index of refraction and undergo multiple scattering in complex domains. It also can automatically capture produced waves (on sufficiently fine grids) near a source (antennas and scatterers) and transfer them to a sequence of coarser grids for efficient long range propagation. Unlike Ray Tracing schemes, the new method propagates entire smooth surfaces, greatly simplifying the computation of solutions over extended domains.

Direct meshless local Petrov–Galerkin (DMLPG) method for time-fractional fourth-order reaction–diffusion problem on complex domains

Social network research and meat reduction – An overview of research directions and results from a study in Denmark

The simulation of nuclear transients using Computational Fluid Dynamics (CFD) presents significant computational challenges due to the inherent complexity and the wide separation in temporal scales between various flow physical phenomena. These disparities lead to high computational costs, often making the simulation of transients impractical without advanced techniques. Consequently, multiple research initiatives are being pursued by the NEAMS thermal-hydraulic area, some driven by academic institutions and some by national laboratories. Overall, they are exploring novel methods to make transient simulations more feasible and efficient. This report delves into recent advancements within the CFD code NekRS, specifically those achieved in Fiscal Year 2024 under the CONNECT effort, aimed at improving the performance and feasibility of transient simulations. The first major advancement involves the porting of NekRS to Aurora, one of the Department of Energy’s (DOE) most powerful supercomputers. Additionally, the report discusses the implementation of an overlapping domain capability within NekRS. This novel GPU-accelerated capability allows different spatial regions of the domain to be solved independently, enhancing the code’s efficiency, particularly when running large-scale simulations in complex domains. The scalability of this approach is demonstrated, highlighting its potential to transform how transients are approached in CFD simulations. Lastly, the report focuses on how this overlapping domain capability specifically accelerates transient simulations through multi-rate timestepping. By decoupling different regions and facilitating faster computations, this method offers a promising pathway to making nuclear transient simulations more computationally feasible, addressing one of the critical bottlenecks in the field. Together, these advancements represent a significant leap forward in transient simulation technology, bringing closer the possibility of handling highly complex nuclear scenarios with greater efficiency and accuracy.

A blob of Newtonian fluid is sandwiched in the narrow gap between two plane parallel surfaces so that, a t some initial instant, its plan-view occupies a simply connected domainD0. Further fluid, with the same material properties, is injected into the gap at some fixed point withinD0, so that the blob begins to grow in size. The domainDoccupied by the fluid at some subsequent time is to be determined.It is shown that the growth is controlled by the existence of an infinite number of invariants of the motion, which are of a purely geometric character. For sufficiently simple initial domainsD0these allow the problem to be reduced to the solution of a finite system of algebraic equations. For more complex initial domains an approximation scheme leads to a similar system of equations to be solved.

Communication in Nursing, 4th Edition

Intersection is one of the most complex and accident-prone urban traffic scenarios for autonomous driving wherein making safe and computationally efficient decisions with high-density traffic flow is usually non-trivial. Current rule-based methods decompose the decision-making task into several serial sub-modules, resulting in long computation time at complex scenarios for on-board computing devices. In this paper, we formulate the decision-making and control problem under intersections as a process of optimal path selection and tracking, where the former selects a path with the best safety measure from a set generated only considering static information, while the latter then considers dynamic obstacles and solve a tracking problem with safety constraints using the chosen path. To avoid the heavy computation introduced by that, we develop a reinforcement learning algorithm called generalized exterior point (GEP) to find a neural network (NN) solution offline. It first constructs a multi-task problem involving all the candidate paths and transforms it into an unconstrained problem with a penalty on safety violations. Afterward, the approximate feasible optimal control policy is obtained by alternatively performing gradient descent and enlarging the penalty. As an exterior point type method, GEP permits control policy to violate inequality constraints during the iterations. To verify the effectiveness of our method, we carried out experiments both in simulation and in a real road test. Results demonstrate that the learned policy can realize collision-free driving under different traffic conditions while reducing the computation time by a large margin.

There is a variety of applications that can benefit from the ability to find optimal or good solutions to a proposed problem automatically. The Artificial Intelligent (AI) community has been actively involved in efficient problem-solving in complex domains such as military or spacecraft problems with successful results. In this paper we describe the integration of AI planning techniques with an existing Workflow Management System. We show how these techniques can improve overall system functionality and can help to automate the definition of business processes. The work is based on a short study carried out at BT Research Laboratories as part of a larger programme that aims to provide technologies for a new generation of business support systems.

Integrating AI planning techniques with workflow management system

Does Migration Motive Matter for Migrants' Employment Outcomes? The Case of Belgium

Homogeneous multicore processors such as the ones proposed by Intel or AMD have become mainstream. However heterogeneous architectures, such as multicore associated with GPUs or with any hardware specialized co-processors usually offer a much higher peak performance/power ratio. When high performance and power efficiency has to be achieved, specialized hardware is often the way to go. Combining a general-purpose multicore with a highly parallel coprocessor, e.g., GPU, allows to both achieve high speedups on parallel sections while maintaining high performance on control sections. However, programming such heterogeneous architectures is quite a challenge for any application developer. The embedded market has been living with it for decades but at a very high programming cost. The general-purpose computing is now entering this era. Manycore performance opens HPC to many new scientific and consumer applications. New multimedia, medical and scientific applications will be developed by hundreds of thousands of engineers across the world. These applications, usually provided by ISV, will have to be tuned for thousands of various platform configurations built with different hardware units such as CPUs, GPUs, accelerators, PCIx buses, memories, etc., each configuration having its own performance profile. Furthermore, in most manycore systems, applications are in competition at run-time for hardware resources like the memory space of accelerators. If ignored this can lead to a global performance slowdown. The past of parallel programming is scattered with hundreds of parallel languages, most of them were designed to address homogeneous architectures and concerned a small and well-trained community of HPC programmers. With the new diversity of parallel hardware platforms and the new community of non-expert developers, expressing parallelism is not sufficient anymore. Resources management, application deployment, and portable performance are interconnected issues that require to be addressed holistically. As many decisions should be taken according to the available hardware, resources management cannot be moved apart from parallel programming. Deploying applications on various systems without having to deal with thousands of configurations is the main concern of ISVs. The grail of parallel computing is to be able to provide portable performance by making hardware changes transparent for a large set of machines and fluctuating execution contexts. Are general-purpose compilers obsolete? Compilers are keystone solutions of any approaches that deal with previous challenges. But general-purpose compilers try to embrace so many domains and try to serve so many constraints that they frequently fail to achieve very high performance. They need to be deeply revisited! Recent techniques are showing promises. Iterative compilation techniques, exploiting the large CPU cycle count now available on every PC, can be used to explore the optimization space at compile-time. Second, machine-learning techniques, e.g. Milepost project ( http://www.milepost.eu/ ), can be used to automatically improve code generation compilers strategies. Speculation can be used to deal with necessary but missing information at compile-time. Finally, dynamic techniques can select or generate at run-time the most efficient code adapted to the execution context and available hardware resources. Future compilers will benefit from past research, but they will also need to combine static and dynamic techniques. Moreover, domain specific approaches might be needed to ensure success. Biography of Francois Bodin Francois Bodin cofounded CAPS (www.caps-entreprise.com) in 2002 while he was a Professor at University of Rennes I and since January 2008 he joined the company as CTO. His contribution includes new approaches for exploiting high performance processors in scientific computing and in embedded applications. Prior to joining CAPS, Francois Bodin held various research positions at University of Rennes I and at the INRIA research lab. He has published over 60 papers in international journals and conferences and he has supervised over 15 PhD thesis. Professor Francois Bodin holds a Master's in CS and a PhD in CS, both from University of Rennes I.

Transition States

Learning automata act in a stochastic environment and are able to update their action probabilities considering the inputs from their environment, so optimizing their functionality as a result. In this paper, the goal is to investigate and evaluate the application of learning automata to cooperation in multi-agent systems, using soccer simulation server as a test bed. Also, because of the large state space of a complex multi-agent domain, it is vital to have a method for environmental states' generalization. In this paper we have introduced and designed a new technique called the "best corner in state square" for generalizing the vast number of states in agent's domain environment to a few number of states by building a virtual grid in that environment. The efficiency of this technique in state space generalization in a cooperative multi-agent domain is investigated

An important part of ensuring continuous development and betterment of performance of a robot soccer team is the process of analyzing past matches and generating insights about possible causes for good or bad outcomes the team has in the field. RoboCup robot soccer matches from leagues such as the 2D Simulation League generate log files that can help create insights using data analysis, but since there is currently no active open collaboration between teams for building an ecosystem of analysis tools, this area is underdeveloped - as a community - and could be improved. We propose an open-source data analysis library that contains all of the basic structures needed for implementing any analysis, as well as a collection of ready-to-use, quasi-agnostic analysis that can be used to analyze matches from any soccer league with little or none adaptation. We believe this can be a common ground for developers from any team to work together in the advancement of technology and lower the barrier of entry into the data analysis realm for teams that are not yet involved in the area. We also demonstrate how this library can be leveraged as a software component for other projects, by building a custom web platform that utilizes it.