Practical applications of multi-agent systems in electric power systems

The transformation of energy networks from passive to active systems requires the embedding of intelligence within the network. One suitable approach to integrating distributed intelligent systems is multi-agent systems technology, where components of functionality run as autonomous agents capable of interaction through messaging. This provides loose coupling between components that can benefit the complex systems envisioned for the smart grid. This paper reviews the key milestones of demonstrated agent systems in the power industry and considers which aspects of agent design must still be addressed for widespread application of agent technology to occur

Realizing networks of proactive smart products

The sheer complexity and number of functionalities embedded in many everyday devices already exceed the ability of most users to learn how to use them effectively. An approach to tackle this problem is to introduce ‘smart’ capabilities in technical products, to enable them to proactively assist and co-operate with humans and other products. In this paper we provide an overview of our approach to realizing networks of proactive and co-operating smart products, starting from the requirements imposed by real-world scenarios. In particular, we present an ontology-based approach to modeling proactive problem solving, which builds on and extends earlier work in the knowledge acquisition community on problem solving methods. We then move on to the technical design aspects of our work and illustrate the solutions, to do with semantic data management and co-operative problem solving, which are needed to realize our functional architecture for proactive problem solving in concrete networks of physical and resource-constrained devices. Finally, we evaluate our solution by showing that it satisfies the quality attributes and architectural design patterns, which are desirable in collaborative multi-agents systems

Enabling Global Price Comparison through Semantic Integration of Web Data

“Sell Globally” and “Shop Globally” have been seen as a potential benefit of web-enabled electronic business. One important step toward realizing this benefit is to know how things are selling in various parts of the world. A global price comparison service would address this need. But there have not been many such services. In this paper, we use a case study of global price dispersion to illustrate the need and the value of a global price comparison service. Then we identify and discuss several technology challenges, including semantic heterogeneity, in providing a global price comparison service. We propose a mediation architecture to address the semantic heterogeneity problem, and demonstrate the feasibility of the proposed architecture by implementing a prototype that enables global price comparison using data from web sources in several countries

An intelligent framework for dynamic web services composition in the semantic web

As Web services are being increasingly adopted as the distributed computing technology of choice to securely publish application services beyond the firewall, the importance of composing them to create new, value-added service, is increasing. Thus far, the most successful practical approach to Web services composition, largely endorsed by the industry falls under the static composition category where the service selection and flow management are done a priori and manually. The second approach to web-services composition aspires to achieve more dynamic composition by semantically describing the process model of Web services and thus making it comprehensible to reasoning engines or software agents. The practical implementation of the dynamic composition approach is still in its infancy and many complex problems need to be resolved before it can be adopted outside the research communities. The investigation of automatic discovery and composition of Web services in this thesis resulted in the development of the eXtended Semantic Case Based Reasoner (XSCBR), which utilizes semantic web and AI methodology of Case Based Reasoning (CBR). Our framework uses OWL semantic descriptions extensively for implementing both the matchmaking profiles of the Web services and the components of the CBR engine. In this research, we have introduced the concept of runtime behaviour of services and consideration of that in Web services selection. The runtime behaviour of a service is a result of service execution and how the service will behave under different circumstances, which is difficult to presume prior to service execution. Moreover, we demonstrate that the accuracy of automatic matchmaking of Web services can be further improved by taking into account the adequacy of past matchmaking experiences for the requested task. Our XSCBR framework allows annotating such runtime experiences in terms of storing execution values of non-functional Web services parameters such as availability and response time into a case library. The XSCBR algorithm for matchmaking and discovery considers such stored Web services execution experiences to determine the adequacy of services for a particular task. We further extended our fundamental discovery and matchmaking algorithm to cater for web services composition. An intensive knowledge-based substitution approach was proposed to adapt the candidate service experiences to the requested solution before suggesting more complex and computationally taxing AI-based planning-based transformations. The inconsistency problem that occurs while adapting existing service composition solutions is addressed with a novel methodology based on Constraint Satisfaction Problem (CSP). From the outset, we adopted a pragmatic approach that focused on delivering an automated Web services discovery and composition solution with the minimum possible involvement of all composition participants: the service provider, the requestor and the service composer. The qualitative evaluation of the framework and the composition tools, together with the performance study of the XSCBR framework has verified that we were successful in achieving our goal

Standardization in cyber-physical systems: the ARUM case

Cyber-physical systems concept supports the realization of the Industrie 4.0 vision towards the computerization of traditional industries, aiming to achieve intelligent and reconfigurable factories. Standardization assumes a critical role in the industrial adoption of cyber-physical systems, namely in the integration of legacy systems as well as the smooth migration from existing running systems to the new ones. This paper analyses some existing standards in related fields and presents identified limitations and efforts for a wider acceptance of such systems by industry. A special attention is devoted to the efforts to develop a standard-compliant service-oriented multi-agent system solution within the ARUM project.info:eu-repo/semantics/publishedVersio

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

From Sensor to Observation Web with Environmental Enablers in the Future Internet

This paper outlines the grand challenges in global sustainability research and the objectives of the FP7 Future Internet PPP program within the Digital Agenda for Europe. Large user communities are generating significant amounts of valuable environmental observations at local and regional scales using the devices and services of the Future Internet. These communities’ environmental observations represent a wealth of information which is currently hardly used or used only in isolation and therefore in need of integration with other information sources. Indeed, this very integration will lead to a paradigm shift from a mere Sensor Web to an Observation Web with semantically enriched content emanating from sensors, environmental simulations and citizens. The paper also describes the research challenges to realize the Observation Web and the associated environmental enablers for the Future Internet. Such an environmental enabler could for instance be an electronic sensing device, a web-service application, or even a social networking group affording or facilitating the capability of the Future Internet applications to consume, produce, and use environmental observations in cross-domain applications. The term ?envirofied? Future Internet is coined to describe this overall target that forms a cornerstone of work in the Environmental Usage Area within the Future Internet PPP program. Relevant trends described in the paper are the usage of ubiquitous sensors (anywhere), the provision and generation of information by citizens, and the convergence of real and virtual realities to convey understanding of environmental observations. The paper addresses the technical challenges in the Environmental Usage Area and the need for designing multi-style service oriented architecture. Key topics are the mapping of requirements to capabilities, providing scalability and robustness with implementing context aware information retrieval. Another essential research topic is handling data fusion and model based computation, and the related propagation of information uncertainty. Approaches to security, standardization and harmonization, all essential for sustainable solutions, are summarized from the perspective of the Environmental Usage Area. The paper concludes with an overview of emerging, high impact applications in the environmental areas concerning land ecosystems (biodiversity), air quality (atmospheric conditions) and water ecosystems (marine asset management)

Multi-Agent Systems

A multi-agent system (MAS) is a system composed of multiple interacting intelligent agents. Multi-agent systems can be used to solve problems which are difficult or impossible for an individual agent or monolithic system to solve. Agent systems are open and extensible systems that allow for the deployment of autonomous and proactive software components. Multi-agent systems have been brought up and used in several application domains

Cognitive Business Process Management for Adaptive Cyber-Physical Processes

In the era of Big Data and Internet-of-Things (IoT), all real-world environments are gradually becoming cyber-physical (e.g., emergency management, healthcare, smart manufacturing, etc.), with the presence of connected devices and embedded ICT systems (e.g., smartphones, sensors, actuators) producing huge amounts of data and events that influence the enactment of the Cyber Physical Processes (CPPs) enacted in such environments. A Process Management System (PMS) employed for executing CPPs is required to automatically adapt its running processes to anomalous situations and exogenous events by minimising any human intervention at run-time. In this paper, we tackle this issue by introducing an approach and an adaptive Cognitive PMS that combines process execution monitoring, unanticipated exception detection and automated resolution strategies leveraging on well-established action-based formalisms in Artificial Intelligence, which allow to interpret the ever-changing knowledge of cyber-physical environments and to adapt CPPs by preserving their base structure.Comment: Preprint from Proceedings of 1st International Workshop on Cognitive Business Process Management (CBPM 2017