Online Build-Order Optimization for Real-Time Strategy Agents Using Multi-Objective Evolutionary Algorithms

The investigation introduces a novel approach for online build-order optimization in real-time strategy (RTS) games. The goal of our research is to develop an artificial intelligence (AI) RTS planning agent for military critical decision- making education with the ability to perform at an expert human level, as well as to assess a players critical decision- making ability or skill-level. Build-order optimization is modeled as a multi-objective problem (MOP), and solutions are generated utilizing a multi-objective evolutionary algorithm (MOEA) that provides a set of good build-orders to a RTS planning agent. We de ne three research objectives: (1) Design, implement and validate a capability to determine the skill-level of a RTS player. (2) Design, implement and validate a strategic planning tool that produces near expert level build-orders which are an ordered sequence of actions a player can issue to achieve a goal, and (3) Integrate the strategic planning tool into our existing RTS agent framework and an RTS game engine. The skill-level metric we selected provides an original and needed method of evaluating a RTS players skill-level during game play. This metric is a high-level description of how quickly a player executes a strategy versus known players executing the same strategy. Our strategic planning tool combines a game simulator and an MOEA to produce a set of diverse and good build-orders for an RTS agent. Through the integration of case-base reasoning (CBR), planning goals are derived and expert build- orders are injected into a MOEA population. The MOEA then produces a diverse and approximate Pareto front that is integrated into our AI RTS agent framework. Thus, the planning tool provides an innovative online approach for strategic planning in RTS games. Experimentation via the Spring Engine Balanced Annihilation game reveals that the strategic planner is able to discover build-orders that are better than an expert scripted agent and thus achieve faster strategy execution times

Guidance, flight mechanics and trajectory optimization. Volume 6 - The N-body problem and special perturbation techniques

Analytical formulations and numerical integration methods for many body problem and special perturbative technique

Insights and guidance for offshore CO2 storage monitoring based on the QICS, ETI MMV, and STEMM-CCS projects

Carbon Capture and Storage (CCS) is a collective term for technologies that allow society to unlock the benefits of energy intensive processes like fertiliser production and combustion of fuels (fossil or biologically sourced) without releasing the CO2 to the atmosphere. Hence, CCS could assist in accelerating decarbonisation while society pursues a just energy transition. This paper aims to summarise the learnings of three research projects that all investigated aspects of marine monitoring for CCS from a CO2 storage operator’s perspective. The QICS (Quantifying and Monitoring Potential Ecosystem Impacts of Geological Carbon Storage), ETI MMV (Energy Technologies Institute Measurement, Monitoring and Verification of CO2 Storage), and STEMM-CCS (Strategies for Environmental Monitoring of Marine CCS) projects collectively represent over twelve years of dedicated research to assess environmental impacts and to develop technologies for detection, location, and quantification of potential leakage from offshore geological storage of CO2. Each project used controlled releases in representative environments to test their methods and technologies. QICS as the first of the three projects, focused on the understanding of sensitivities of the UK marine environment to a potential leak from a CO2 storage complex and tested technologies to detect such emissions. The ETI MMV project brought together research and industry partners to develop and sea trial an operational, integrated and cost-effective marine monitoring system for geological CO2 storage. As a commercial project, these results have never been published before and this paper shares for the first-time insights from this work. In February 2020, STEMM-CCS, completed its quest to test techniques for environmental monitoring over a marine CO2 storage site in the UK North Sea, further improved near seabed leakage characterisation capabilities, and delivered a first marine CCS demonstration level ecological baseline. This paper aims to summarise some of the key insights from the three projects and provides references where available for the interested reader. The key finding of all three projects is that the impacts of small to medium CO2 leakages from large-scale storage are limited and localised. Technology capabilities exist for integrated marine CO2 storage monitoring and their performance has been benchmarked at controlled release trials. Even small leakages of 10− 50 L/min can be detected at unknown locations in a large area of interest. Finally, the first important steps towards automated monitoring data analysis have been made, including automated leakage signal detection from Side Scan Sonar data (ETI MMV project) and automated species identification from marine biology images (STEMM-CCS project). Some remaining challenges include missed/ false alerts because of large variations in the background signal, the cost of monitoring large areas over long periods, and making real-time decisions based on big data. Continued work to reduce the cost of marine monitoring technologies and advancing automation of data processing and analysis will be important in order to support safe and efficient offshore CCS deployment at large scale

Chebyshev polynomial filtered subspace iteration in the Discontinuous Galerkin method for large-scale electronic structure calculations

The Discontinuous Galerkin (DG) electronic structure method employs an adaptive local basis (ALB) set to solve the Kohn-Sham equations of density functional theory (DFT) in a discontinuous Galerkin framework. The adaptive local basis is generated on-the-fly to capture the local material physics, and can systematically attain chemical accuracy with only a few tens of degrees of freedom per atom. A central issue for large-scale calculations, however, is the computation of the electron density (and subsequently, ground state properties) from the discretized Hamiltonian in an efficient and scalable manner. We show in this work how Chebyshev polynomial filtered subspace iteration (CheFSI) can be used to address this issue and push the envelope in large-scale materials simulations in a discontinuous Galerkin framework. We describe how the subspace filtering steps can be performed in an efficient and scalable manner using a two-dimensional parallelization scheme, thanks to the orthogonality of the DG basis set and block-sparse structure of the DG Hamiltonian matrix. The on-the-fly nature of the ALBs requires additional care in carrying out the subspace iterations. We demonstrate the parallel scalability of the DG-CheFSI approach in calculations of large-scale two-dimensional graphene sheets and bulk three-dimensional lithium-ion electrolyte systems. Employing 55,296 computational cores, the time per self-consistent field iteration for a sample of the bulk 3D electrolyte containing 8,586 atoms is 90 seconds, and the time for a graphene sheet containing 11,520 atoms is 75 seconds.Comment: Submitted to The Journal of Chemical Physic

A Review of Scanning Tunneling Microscope and Atomic Force Microscope Imaging of Large Biological Structures: Problems and Prospects

The application of the scanning tunneling microscope (STM) and the atomic force microscope (AFM) to the study of small biological molecules, such as DNA and smaller molecules, has received considerable attention in the literature. This paper reviews STM and AFM studies of larger biological structures such as bacterial membranes, bacteriophages, viruses, antibodies, etc. The problems encountered in these applications are emphasized, with particular reference to the unknown conduction mechanism, tip-sample interaction forces, and tip-sample convolution artifacts in the images. The latter problem is illustrated by new results from IgG antibody complexes attached to a bacterial sheath layer. A new conduction mechanism involving a graphite film overlayer is suggested. The future prospects are discussed, with emphasis on the unique capabilities of these microscopes compared to conventional electron microscopes

The Value of Information Technology-Enabled Diabetes Management

Reviews different technologies used in diabetes disease management, as well as the costs, benefits, and quality implications of technology-enabled diabetes management programs in the United States

How young people from culturally and linguistically diverse backgrounds experience mental health: some insights for mental health nurses

This article reports on a part of a study which looked at the mental health of culturally and linguistically diverse (CALD) young people. The research sought to learn from CALD young people, carers, and service providers experiences relevant to the mental health of this group of young people. The ultimate goal was to gain insights that would inform government policy, service providers, ethnic communities and most importantly the young people themselves. To this end, qualitative interviews were undertaken with 123 CALD young people, 41 carers and 14 mental health service providers in Queensland, Western Australia and South Australia. Only one aspect of the study will be dealt with here, namely the views of the young CALD participants, which included risk factors, coping strategies and recommendations about how they could be supported in their struggle to maintain mental health. One of the most important findings of the study relates to the resilience of these young people and an insight into the strategies that they used to cope. The efforts of these young people to assist us in our attempts to understand their situation deserve to be rewarded by improvements in the care that we provide. To this end this article sets out to inform mental health nurses of the results of the study so that they will be in a position to better understand the needs and strengths of their CALD clients and be in a better position to work effectively with them