Technological roadmap on AI planning and scheduling

At the beginning of the new century, Information Technologies had become basic and indispensable constituents of the production and preparation processes for all kinds of goods and services and with that are largely influencing both the working and private life of nearly every citizen. This development will continue and even further grow with the continually increasing use of the Internet in production, business, science, education, and everyday societal and private undertaking. Recent years have shown, however, that a dramatic enhancement of software capabilities is required, when aiming to continuously provide advanced and competitive products and services in all these fast developing sectors. It includes the development of intelligent systems – systems that are more autonomous, flexible, and robust than today’s conventional software. Intelligent Planning and Scheduling is a key enabling technology for intelligent systems. It has been developed and matured over the last three decades and has successfully been employed for a variety of applications in commerce, industry, education, medicine, public transport, defense, and government. This document reviews the state-of-the-art in key application and technical areas of Intelligent Planning and Scheduling. It identifies the most important research, development, and technology transfer efforts required in the coming 3 to 10 years and shows the way forward to meet these challenges in the short-, medium- and longer-term future. The roadmap has been developed under the regime of PLANET – the European Network of Excellence in AI Planning. This network, established by the European Commission in 1998, is the co-ordinating framework for research, development, and technology transfer in the field of Intelligent Planning and Scheduling in Europe. A large number of people have contributed to this document including the members of PLANET non- European international experts, and a number of independent expert peer reviewers. All of them are acknowledged in a separate section of this document. Intelligent Planning and Scheduling is a far-reaching technology. Accepting the challenges and progressing along the directions pointed out in this roadmap will enable a new generation of intelligent application systems in a wide variety of industrial, commercial, public, and private sectors

Air Force Institute of Technology Research Report 1997

This report summarizes the research activities of the Air Force Institute of Technology\u27s Graduate School of Engineering and the Graduate School of Logistics and Acquisition Management. It describes research interests and faculty expertise; list student theses/dissertations; identifies research sponsors and contributions; and outlines the procedure for contacting either school

Proceedings of the XIII Global Optimization Workshop: GOW'16

[Excerpt] Preface: Past Global Optimization Workshop shave been held in Sopron (1985 and 1990), Szeged (WGO, 1995), Florence (GO’99, 1999), Hanmer Springs (Let’s GO, 2001), Santorini (Frontiers in GO, 2003), San José (Go’05, 2005), Mykonos (AGO’07, 2007), Skukuza (SAGO’08, 2008), Toulouse (TOGO’10, 2010), Natal (NAGO’12, 2012) and Málaga (MAGO’14, 2014) with the aim of stimulating discussion between senior and junior researchers on the topic of Global Optimization. In 2016, the XIII Global Optimization Workshop (GOW’16) takes place in Braga and is organized by three researchers from the University of Minho. Two of them belong to the Systems Engineering and Operational Research Group from the Algoritmi Research Centre and the other to the Statistics, Applied Probability and Operational Research Group from the Centre of Mathematics. The event received more than 50 submissions from 15 countries from Europe, South America and North America. We want to express our gratitude to the invited speaker Panos Pardalos for accepting the invitation and sharing his expertise, helping us to meet the workshop objectives. GOW’16 would not have been possible without the valuable contribution from the authors and the International Scientific Committee members. We thank you all. This proceedings book intends to present an overview of the topics that will be addressed in the workshop with the goal of contributing to interesting and fruitful discussions between the authors and participants. After the event, high quality papers can be submitted to a special issue of the Journal of Global Optimization dedicated to the workshop. [...

Knowledge engineering techniques for automated planning

Formulating knowledge for use in AI Planning engines is currently some-thing of an ad-hoc process, where the skills of knowledge engineers and the tools they use may significantly influence the quality of the resulting planning application. There is little in the way of guidelines or standard procedures, however, for knowledge engineers to use when formulating knowledge into planning domain languages such as PDDL. Also, there is little published research to inform engineers on which method and tools to use in order to effectively engineer a new planning domain model. This is of growing importance, as domain independent planning engines are now being used in a wide range of applications, with the consequence that op-erational problem encodings and domain models have to be developed in a standard language. In particular, at the difficult stage of domain knowledge formulation, changing a statement of the requirements into something for-mal - a PDDL domain model - is still somewhat of an ad hoc process, usually conducted by a team of AI experts using text editors. On the other hand, the use of tools such as itSIMPLE or GIPO, with which experts gen-erate a high level diagrammatic description and automatically generate the domain model, have not yet been proven to be more effective than hand coding. The major contribution of this thesis is the evaluation of knowledge en-gineering tools and techniques involved in the formulation of knowledge. To support this, we introduce and encode a new planning domain called Road Traffic Accidents (RTA), and discuss a set of requirements that we have derived, in consultation with stakeholders and analysis of accident management manuals, for the planning part of the management task. We then use and evaluate three separate strategies for knowledge formulation, encoding domain models from a textual, structural description of require-ments using (i) the traditional method of a PDDL expert and text editor (ii) a leading planning GUI with built in UML modelling tools (iii) an object-based notation inspired by formal methods. We evaluate these three ap-proaches using process and product metrics. The results give insights into the strengths and weaknesses of the approaches, highlight lessons learned regarding knowledge encoding, and point to important lines of research for knowledge engineering for planning. In addition, we discuss a range of state-of-the-art modelling tools to find the types of features that the knowledge engineering tools possess. These features have also been used for evaluating the methods used. We bench-mark our evaluation approach by comparing it with the method used in the previous International Competition for Knowledge Engineering for Plan-ning & Scheduling (ICKEPS). We conclude by providing a set of guide-lines for building future knowledge engineering tools

Risk Assessment in Air Traffic Management

One of the most complex challenges for the future of aviation is to ensure a safe integration of the expected air traffic demand. Air traffic is expected to almost double its current value in 20 years, which cannot be managed without the development and implementation of a safe air traffic management (ATM) system. In ATM, risk assessment is a crucial cornerstone to validate the operation of air traffic flows, airport processes, or navigation accuracy. This book tries to be a focal point and motivate further research by encompassing crosswise and widespread knowledge about this critical and exciting issue by bringing to light the different purposes and methods developed for risk assessment in ATM

Avian influenza and co-infections : investigation of the interactions in the poultry models

The purpose of this study was to assess the burden of co-infections in the field and to better understand the possible synergism between pathogens in a laboratory setting. We focussed on E. coli (O78) and low pathogenic avian influenza virus (LPAIV, H6N1) in turkey model and infected the birds via the aerosol route to reproduce respiratory disease. Viral shedding and lesions were more severe and persisted longer during coinfection indicating possible enhancement of pathogenesis for LPAIV by E. coli and vice versa. These findings all endorse our conclusions that E. coli and LPAIV exercise an additive pathogenic effect in the reproduction of respiratory disease if given simultaneously or spaced by three days between the viral and the bacterial challenges to susceptible turkeys. In parallel, we studied avian respiratory agents circulating in the field in Pakistani farms. There, we focussed on co-infections as well, targeting viruses only as a first study. We observed frequent LPAIV H9 (G1 lineage) and Newcastle disease virus (genotype VII) coinfections in the field

Blockchain-Based Digitalization of Logistics Processes—Innovation, Applications, Best Practices

Blockchain technology is becoming one of the most powerful future technologies in supporting logistics processes and applications. It has the potential to destroy and reorganize traditional logistics structures. Both researchers and practitioners all over the world continuously report on novel blockchain-based projects, possibilities, and innovative solutions with better logistic service levels and lower costs. The idea of this Special Issue is to provide an overview of the status quo in research and possibilities to effectively implement blockchain-based solutions in business practice. This Special Issue reprint contained well-prepared research reports regarding recent advances in blockchain technology around logistics processes to provide insights into realized maturity