Special issue: Development of service-based and agent-based computing systems

This special issue presents the best papers from theworkshops onService-OrientedComputing: Agents, Semantics and Engineering (SOCASE 2010) held in May 2010 in Toronto, Canada and the IEEE 2010 First International Workshop on Service-Oriented Computing and Multi-Agent Systems (SOCMAS 2010) held in July 2010 in Miami, Florida, USA. The goal of the workshops was to present the recent significant developments at the intersections of multi-agent systems, semantic technology, and service-oriented computing, and to promote crossfertilization of techniques. In particular, the workshops attempted to identify techniques from research on multi-agent systems and semantic technology that will have the greatest impact on automating serviceoriented application construction and management, focusing on critical challenges such as service quality assurance, reliability, and adaptability. The areas of service-oriented computing and Semantic Web services offer much of real interest to the multi-agent system community, including similarities in system architectures and provision processes, powerful tools, and the focus on many related issues including quality of service, security, and reliability. In addition, service-oriented computing and Semantic Web services offer various diverse application fields for both the concepts and methodologies of intelligent agent and multi-agent systems. Similarly, techniques developed in the multi-agent systems research community promise to have a strong impact on this fast growing technology. In particular, they enable services to be discovered and enacted across enterprise boundaries. If an organisation bases its success on services provided by others, then it must be able to trust that the services will perform as promised, whenever needed. Researchers in multi-agent systems have investigated such trust mechanisms

Multifrequency-coupled oscillators for distributed multiagent coordination

The coordination of multiagent systems in real environments receives considerable attention from research and industry. The design of coordination mechanisms should take into account the nature of the environment where the system is embedded. In this paper, the multiagent system is in an environment that features periodic properties. This environment is approached from a signal processing point of view to extract such properties. The coordination is performed by the proposed multifrequency-coupled oscillators (MuFCO) algorithm. It addresses the coordination of the multiagent system as a distributed collective synchronization mechanism. An operation example of MuFCO algorithm is shown, where it is used to coordinate consumptions in a smart grid. Thanks to the MuFCO algorithm, themultiagent system can be used to smooth the aggregated consumption of an electrical grid in a distributed way

Implementation Of A Novel Cooperative Protocol for Distributed Voltage Control in Active Distribution Networks

Microgrids are small localized grids that help to integrate many renewable-energy sources into the main electric grid. Microgrids can also operate separately from the main electric grid during faults to enhance the customers reliability. For a successful integration of microgrids we need to control the voltage at the distributed generation units in order to achieve the required sharing of reactive power. For this purpose a multiagent based distributed control scheme is implemented in this thesis. The objective of this thesis is to design and implement a multiagent system for the microgrid that has distributed battery energy storage systems (BESS) and renewable distributed generation (DG) units. The proposed multiagent system has been designed to coordinate among distributed generation (DG) units to control voltage. Multiagent system is composed of multiple agents that communicate to solve problems. The proposed multiagent system for the control of microgrid has been implemented on Texas Instruments Tiva-C controller boards. The real time simulator Opal-RT has been used to create a microgrid model. Hardware testing is done in real time

Task-Based Information Compression for Multi-Agent Communication Problems with Channel Rate Constraints

A collaborative task is assigned to a multiagent system (MAS) in which agents are allowed to communicate. The MAS runs over an underlying Markov decision process and its task is to maximize the averaged sum of discounted one-stage rewards. Although knowing the global state of the environment is necessary for the optimal action selection of the MAS, agents are limited to individual observations. The inter-agent communication can tackle the issue of local observability, however, the limited rate of the inter-agent communication prevents the agent from acquiring the precise global state information. To overcome this challenge, agents need to communicate their observations in a compact way such that the MAS compromises the minimum possible sum of rewards. We show that this problem is equivalent to a form of rate-distortion problem which we call the task-based information compression. We introduce a scheme for task-based information compression titled State aggregation for information compression (SAIC), for which a state aggregation algorithm is analytically designed. The SAIC is shown to be capable of achieving near-optimal performance in terms of the achieved sum of discounted rewards. The proposed algorithm is applied to a rendezvous problem and its performance is compared with several benchmarks. Numerical experiments confirm the superiority of the proposed algorithm.Comment: 13 pages, 9 figure

Embedded intelligence for electrical network operation and control

Integrating multiple types of intelligent, mulitagent data analysis within a smart grid can pave the way for flexible, extensible, and robust solutions to power network management