20,630 research outputs found
Towards engineering ontologies for cognitive profiling of agents on the semantic web
Research shows that most agent-based collaborations
suffer from lack of flexibility. This is due to the fact that
most agent-based applications assume pre-defined
knowledge of agents’ capabilities and/or neglect basic
cognitive and interactional requirements in multi-agent
collaboration. The highlight of this paper is that it brings
cognitive models (inspired from cognitive sciences and HCI)
proposing architectural and knowledge-based requirements
for agents to structure ontological models for cognitive
profiling in order to increase cognitive awareness between
themselves, which in turn promotes flexibility, reusability
and predictability of agent behavior; thus contributing
towards minimizing cognitive overload incurred on humans.
The semantic web is used as an action mediating space,
where shared knowledge base in the form of ontological
models provides affordances for improving cognitive
awareness
Densifying the sparse cloud SimSaaS: The need of a synergy among agent-directed simulation, SimSaaS and HLA
Modelling & Simulation (M&S) is broadly used in real scenarios where making
physical modifications could be highly expensive. With the so-called Simulation
Software-as-a-Service (SimSaaS), researchers could take advantage of the huge
amount of resource that cloud computing provides. Even so, studying and
analysing a problem through simulation may need several simulation tools, hence
raising interoperability issues. Having this in mind, IEEE developed a standard
for interoperability among simulators named High Level Architecture (HLA).
Moreover, the multi-agent system approach has become recognised as a convenient
approach for modelling and simulating complex systems. Despite all the recent
works and acceptance of these technologies, there is still a great lack of work
regarding synergies among them. This paper shows by means of a literature
review this lack of work or, in other words, the sparse Cloud SimSaaS. The
literature review and the resulting taxonomy are the main contributions of this
paper, as they provide a research agenda illustrating future research
opportunities and trends
Simulation of the Long-Term Effects of Decentralized and Adaptive Investments in Cross-Agency Interoperable and Standard IT Systems
Governments have come under increasing pressure to promote horizontal flows of information across agencies, but investment in cross-agency interoperable and standard systems have been minimally made since it seems to require government agencies to give up the autonomies in managing own systems and its outcomes may be subject to many external and interaction risks. By producing an agent-based model using 'Blanche' software, this study provides policy-makers with a simulation-based demonstration illustrating how government agencies can autonomously and interactively build, standardize, and operate interoperable IT systems in a decentralized environment. This simulation designs an illustrative body of 20 federal agencies and their missions. A multiplicative production function is adopted to model the interdependent effects of heterogeneous systems on joint mission capabilities, and six social network drivers (similarity, reciprocity, centrality, mission priority, interdependencies, and transitivity) are assumed to jointly determine inter-agency system utilization. This exercise simulates five policy alternatives derived from joint implementation of three policy levers (IT investment portfolio, standardization, and inter-agency operation). The simulation results show that modest investments in standard systems improve interoperability remarkably, but that a wide range of untargeted interoperability with lagging operational capabilities improves mission capability less remarkably. Nonetheless, exploratory modeling against the varying parameters for technology, interdependency, and social capital demonstrates that the wide range of untargeted interoperability responds better to uncertain future states and hence reduces the variances of joint mission capabilities. In sum, decentralized and adaptive investments in interoperable and standard systems can enhance joint mission capabilities substantially and robustly without requiring radical changes toward centralized IT management.Public IT Investment, Interoperability, Standardization, Social Network, Agent-Based Modeling, Exploratory Modeling
An Analysis of Service Ontologies
Services are increasingly shaping the world’s economic activity. Service provision and consumption have been profiting from advances in ICT, but the decentralization and heterogeneity of the involved service entities still pose engineering challenges. One of these challenges is to achieve semantic interoperability among these autonomous entities. Semantic web technology aims at addressing this challenge on a large scale, and has matured over the last years. This is evident from the various efforts reported in the literature in which service knowledge is represented in terms of ontologies developed either in individual research projects or in standardization bodies. This paper aims at analyzing the most relevant service ontologies available today for their suitability to cope with the service semantic interoperability challenge. We take the vision of the Internet of Services (IoS) as our motivation to identify the requirements for service ontologies. We adopt a formal approach to ontology design and evaluation in our analysis. We start by defining informal competency questions derived from a motivating scenario, and we identify relevant concepts and properties in service ontologies that match the formal ontological representation of these questions. We analyze the service ontologies with our concepts and questions, so that each ontology is positioned and evaluated according to its utility. The gaps we identify as the result of our analysis provide an indication of open challenges and future work
Knowledge formalization in experience feedback processes : an ontology-based approach
Because of the current trend of integration and interoperability of industrial systems, their size and complexity continue to grow making it more difficult to analyze, to understand and to solve the problems that happen in their organizations. Continuous improvement methodologies are powerful tools in order to understand and to solve problems, to control the effects of changes and finally to capitalize knowledge about changes and improvements. These tools involve suitably represent knowledge relating to the concerned system. Consequently, knowledge management (KM) is an increasingly important source of competitive advantage for organizations. Particularly, the capitalization and sharing of knowledge resulting from experience feedback are elements which play an essential role in the continuous improvement of industrial activities. In this paper, the contribution deals with semantic interoperability and relates to the structuring and the formalization of an experience feedback (EF) process aiming at transforming information or understanding gained by experience into explicit knowledge. The reuse of such knowledge has proved to have significant impact on achieving themissions of companies. However, the means of describing the knowledge objects of an experience generally remain informal. Based on an experience feedback process model and conceptual graphs, this paper takes domain ontology as a framework for the clarification of explicit knowledge and know-how, the aim of which is to get lessons learned descriptions that are significant, correct and applicable
Interoperability in health care
With the advancement of technology, patient information has been being computerized in order to facilitate the work of healthcare professionals and improve the quality of healthcare delivery. However, there are many heterogeneous information systems that need to communicate, sharing information and making it available when and where it is needed. To respond to this requirement the Agency for Integration, Diffusion, and Archiving of medical information (AIDA) was created, a multi-agent and service-based platform that ensures interoperability among healthcare information systems. In order to improve the performance of the platform, beyond the SWOT analysis performed, a system to prevent failures that may occur in the platform database and also in machines where the agents are executed was created. The system has been implemented in the Centro Hospitalar do Porto (one of the major Portuguese hospitals), and it is now possible to define critical workload periods of AIDA, improving high availability and load balancing. This is explored in this chapter.(undefined
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