Field Based Coordination For Pervasive Multiagent Systems

Field-based Coordination for Pervasive Multi-agent Systems

Field-Based Coordination for Pervasive Multiagent Systems

More and more, software systems involve autonomous and distributed software components that have to execute and interact in open and dynamic environments, such as in pervasive, autonomous, and mobile applications. The requirements with respect to dynamics, openness, scalability, and decentralization call for new approaches to software design and development, capable of supporting spontaneous configuration, tolerating partial failures, or arranging adaptive reorganization of the whole system. Inspired by the behaviour of complex natural systems, scientists and engineers have started to adjust their mechanisms and techniques for self-organization and adaption to changing environments. In line with these considerations, Mamei and Zambonelli propose an interaction model inspired by the way masses and particles in our universe move and self-organize according to contextual information represented by gravitational and electromagnetic fields. The key idea is to have the components’ actions driven by computational force fields, generated by the components themselves or by some infrastructures, and propagated across the environment. Together with its supporting middleware infrastructure – available with additional information under http://www.agentgroup.unimore.it – this model can serve as the basis for a general purpose and widely applicable approach for the design and development of adaptive distributed applications.

Architecture-Based Design of Multi-Agent Systems

Multi-agent systems are claimed to be especially suited to the development of software systems that are decentralized, can deal flexibly with dynamic conditions, and are open to system components that come and go. This is why they are used in domains such as manufacturing control, automated vehicles, and e-commerce markets. Danny Weyns' book is organized according to the postulate that "developing multi-agent systems is 95% software engineering and 5% multi-agent systems theory." He presents a software engineering approach for multi-agent systems that is heavily based on software architecture - with, for example, tailored patterns such as "situated agent", "virtual environment", and "selective perception" - and on middleware for distributed coordination – with programming abstractions such as "views" and "roles." Next he shows the feasibility and applicability of this approach with the development of an automated transportation system consisting of a number of automatic guided vehicles transporting loads in an industrial setting. Weyns puts the development of multi-agent systems into a larger perspective with traditional software engineering approaches. With this, he opens up opportunities to exploit the body of knowledge developed in the multi-agent systems community to tackle some of the difficult challenges of modern-day software systems, such as decentralized control, location-awareness, self-adaption, and large-scale. Thus his book is of interest for both researchers and industrial software engineers who develop applications in areas such as distributed control systems and mobile applications where such requirements are of crucial importance.