A reusable iterative optimization software library to solve combinatorial problems with approximate reasoning

Real world combinatorial optimization problems such as scheduling are typically too complex to solve with exact methods. Additionally, the problems often have to observe vaguely specified constraints of different importance, the available data may be uncertain, and compromises between antagonistic criteria may be necessary. We present a combination of approximate reasoning based constraints and iterative optimization based heuristics that help to model and solve such problems in a framework of C++ software libraries called StarFLIP++. While initially developed to schedule continuous caster units in steel plants, we present in this paper results from reusing the library components in a shift scheduling system for the workforce of an industrial production plant.Comment: 33 pages, 9 figures; for a project overview see http://www.dbai.tuwien.ac.at/proj/StarFLIP

Target Apps Selection: Towards a Unified Search Framework for Mobile Devices

With the recent growth of conversational systems and intelligent assistants such as Apple Siri and Google Assistant, mobile devices are becoming even more pervasive in our lives. As a consequence, users are getting engaged with the mobile apps and frequently search for an information need in their apps. However, users cannot search within their apps through their intelligent assistants. This requires a unified mobile search framework that identifies the target app(s) for the user's query, submits the query to the app(s), and presents the results to the user. In this paper, we take the first step forward towards developing unified mobile search. In more detail, we introduce and study the task of target apps selection, which has various potential real-world applications. To this aim, we analyze attributes of search queries as well as user behaviors, while searching with different mobile apps. The analyses are done based on thousands of queries that we collected through crowdsourcing. We finally study the performance of state-of-the-art retrieval models for this task and propose two simple yet effective neural models that significantly outperform the baselines. Our neural approaches are based on learning high-dimensional representations for mobile apps. Our analyses and experiments suggest specific future directions in this research area.Comment: To appear at SIGIR 201

NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 9: Information intermediaries and the transfer of aerospace Scientific and Technical Information (STI): A report from the field

From the NASA/DOD survey data, there can be no way of inferring what strategy for knowledge transfer is best; indeed, given the fact that the respondents were all presumably well qualified professionals, the data tend to call into serious question the idea that any one model might meet the needs of more than a distinct minority of possible users. The evidence to date appears to reinforce the concept that different information environments take many different shapes, and interact with each other and with formal data transmission sources in many different and equally valuable ways. Any overall strategy for improving the effectiveness and efficiency of scientific and technical information sharing must take this divergence into account, and work toward the creation of systems that reinforce true interactive knowledge utilization rather than simply disseminating data

Aspects of cooperating agents

An overview on aspects about cooperating agents is presented. As multiagent systems are various, we start with a classification of multiagent systems which is particularly influenced by an article from Decker, Durfee, and Lesser [Decker& 89]. In the following, the aspects of communication, planning, and negotiation are examined. On the occasion of communication, the discussion is split into: no communication - simple protocols - artificial languages. The planning aspect is broken into sections: from classical to multiagent planning - a general multiagent planning theory - intention - intention-directed multiagent planning. Finally, a summary of Brigitte and Hassan Lâasri and Victor Lesser\u27s negotiation theory will be presented

A survey of QoS-aware web service composition techniques

Web service composition can be briefly described as the process of aggregating services with disparate functionalities into a new composite service in order to meet increasingly complex needs of users. Service composition process has been accurate on dealing with services having disparate functionalities, however, over the years the number of web services in particular that exhibit similar functionalities and varying Quality of Service (QoS) has significantly increased. As such, the problem becomes how to select appropriate web services such that the QoS of the resulting composite service is maximized or, in some cases, minimized. This constitutes an NP-hard problem as it is complicated and difficult to solve. In this paper, a discussion of concepts of web service composition and a holistic review of current service composition techniques proposed in literature is presented. Our review spans several publications in the field that can serve as a road map for future research

The multi-agent system architecture in SEWASIE

We describe the design, implementation and deployment of the multi-level agent-based system architecture developed for the SEWASIE project. The aim of the system is to help the user in querying heterogeneous data sources which are integrated by means of ontologies. The agent architecture is based on a two level data integration scheme supported by mediators and brokers, connected by a peer to peer mechanism. Implementation is done on top of the JADE system, a modular and scalable platform that satisfies FIPA standards.Facultad de Informátic

ECONOMICS OF DETECTION AND CONTROL OF INVASIVE SPECIES: WORKSHOP HIGHLIGHTS

Invasive species are species that are not native to an ecosystem, and when introduced into the new ecosystem, they cause economic or environmental damage. Trade is one way in which these species are introduced into new regions, and as trade increases, the introduction of invasive species also rises. The Center for Agricultural Policy and Trade Studies, North Dakota State University, held a workshop on April 30, 2004 in Fargo, ND, titled ?Economics of Detection and Control of Invasive Species? to address these issues. The purpose of this workshop was to present current findings on the subject of invasive species in agricultural trade and to structure the model for an in-depth research project examining this issue. Speakers included experts from the Animal Plant Health Inspection Service and the Economic Research Service of the U.S. Department of Agriculture and from U.S. Customs and Border Patrol, as well as professors of economics from North Dakota State University and other academic institutions. Discussion included the impact of invasive species on agricultural production and trade, the tools used by the U.S. Department of Agriculture and U.S. Customs and Border patrol to detect and control incoming species, and the creation of econometric models to capture and explain these processes and to analyze policy issues. This report contains abstracts from the presentations given at the workshop.Resource /Energy Economics and Policy,

Adaptive search in mobile peer-to-peer databases

Information is stored in a plurality of mobile peers. The peers communicate in a peer to peer fashion, using a short-range wireless network. Occasionally, a peer initiates a search for information in the peer to peer network by issuing a query. Queries and pieces of information, called reports, are transmitted among peers that are within a transmission range. For each search additional peers are utilized, wherein these additional peers search and relay information on behalf of the originator of the search