Constantin Zamfirescu

On the design of emergent systems: an investigation of integration and interoperability issues

Abstract Many useful manmade systems in this world are extremely complex; a typical example is a large infrastructure. No design team ever invents these artifacts because they are too complex. These artifacts are made by combining existing elements (legacy) and by building new subsystems without explicit and comprehensive up-front coordination. To a large extent, these complex systems emerge and evolve. Experience shows that designers frequently fail to develop artifacts that, when combined, facilitate the emergence of effective and efficient systems. This paper formally elaborates the mechanism behind this phenomenon, and proposes principles for the design of components for emergent systems. The above insights were gained during the development of research prototypes for multi-agent manufacturing control; manufacturing systems are notorious for experiencing integration and interoperability problems as described above. Consequently, the design principles are discussed and illustrated on the design of multi-agent manufacturing control systems but also on work by others. Finally, although this paper mainly discusses the above in a generic fashion, and although the generic statements hold in an application-independent manner, it is important to appreciate that the applicability of the above insights and principles has significant limitations, which are discussed in the paper.

Self-organising in multi-agent coordination and control using stigmergy

In order to cope with todays dynamic environment, the described manufacturing control system is designed as a self-organising multi-agent system. The design of this novel system implements the PROSA reference architecture [1]. Coordination among agents is done indirectly through a pheromone-based dissipative field as is done by social insects in coordinating their behaviour. In this case, our agents act as social insects interpreting the pheromones put by the others in the environment. This control system is built from the basic elements of any manufacturing controller, namely products, resources and orders. However, the overall control system is constructed not only from those basic elements but also employing the appropriate interaction patterns among the agents who represent them. For coordination purposes, the agents send out a kind of mobile agents - artificial ants - to lay down information on the environment. In our case, where fulfilling the manufacturing orders is the main concern, there are at least 3 types of ant in this system: (1) feasibility ants - to propagate information concerning the feasible finishing routes; (2) exploring ants - to explore the feasible routes; and (3) intention ants - to propagate the route preferences. The overall mechanism enables the system to exhibit a self-organising behaviour.

Emergent forecasting using a stigmergy approach in manufacturing coordination and control

This paper presents the design of new manufacturing coordination and control systems based on multi-agent technology. This design aims to cope with a dynamic environment characteristic for manufacturing systems nowadays. One important feature to handle these dynamics is having the ability to plan ahead, thus avoiding problems before they occur. Therefore, one novel characteristic of the system is the ability to perform emergent forecasting. Regarding emergent forecasting, an important issue that rises from this design is how to ensure that the forecast is reliable, and on the other hand, that the system is still fast enough to react against disturbances. This paper elaborates on the agents that form the system, and proposes a way to engineer it. Moreover, this paper also describes emergent forecasting. In addition to that, the trade off between responsiveness and forecast reliability (system nervousness issue) is also discussed in this paper, altogether with an example on the design of social acceptable behaviour that aims to handle the nervousness issue. Finally, some implementation and prototyping results are presented.

Multi-Agent Manufacturing Control: An Industrial Case Study

Abstract The paper discusses the development of a multi-agent manufacturing control system for an industrial application. This multi-agent system follows the PROSA reference architecture and applies ail ant colony design (stigmergy) to provide coordination and emergent forecasting services. The paper first presents the experimental set-up: • The properties of this shop and its particular challenges to control systems • The emulation of an existing production shop in industry • The multi-agent system connected to this emulation Next, the paper discusses the real-time aspect of the emulation. Third, the multiagent control system is presented. Filially, the paper discusses the browser to analyze the results generated during simulation runs

A Case Study for Modular Plant Control.

This paper reports on an engineering approach to address the growing need for managing highly modular plants. An implemented agent-based manufacturing controller, inspired by ant social behavior, is presented and discussed. The work aims to provide the key engineering concerns on how the impact of variations in production resources, factory organization and planning processes can be smoothly tackled in respect of plant performance criteria. The insights are drawn along our experience carried out in the MPA (Modular Plant Architecture) project, which is part of the 5 th EU framework program.

Supporting self-facilitation in distributed group decisions

The paper addresses the problem of supporting self-facilitation of distributed autonomous groups of decision-makers from an agent-oriented perspective. In contrast to monolithic designs based on functional decomposition, it is argued that an agent-oriented approach is the appropriate means to provide better support for group meetings. The focus is on distributed and asynchronous meetings, detailing the conceptual modelling aspects of an implemented agent-based GDSS which exhibits an emergent functionality able to support in an effective way the dynamics of the group decision process.

Genetic Algorithms: A Decision Tool in Industrial Disassembly

In the recycling process of the Waste Electrical and Electronic Equipment (WEEE) the disassembly process has a central role. Disassembly is not the reverse of the assembly process, real difficulties occur in the tasks assignment process of the disassembly operations. Since this is a multi objective optimization problem, we prove that genetic algorithms provide a useful multi-criteria decision tool in the industrial disassembly process.