Olaf Bochmann

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.

Multi-agent Coordination and Control Using Stigmergy Applied to Manufacturing Control

This manuscript discusses multi-agent coordination and control using techniques inspired by the behavior of social insects. It presents a system design that enables desirable overall behavior to emerge without exposing the individual agents to the complexity and dynamics of the overall system. The research, which this paper discusses, focuses on manufacturing control. However, the approach remains applicable to the coordination and control of other types of ironware systems (e.g. traffic, supply chain...).

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

Supply network control, an engineering perspective

Abstract This paper presents an engineering perspective on the supply network coordination problem. This manuscript treats the coordination as an ongoing task and takes disturbances and exceptions as business as usual. A manufacturing control and coordination mechanism based on PROSA and ants is used as base for the overall coordination of the supply network. Reputation serves to enforce the social behaviour among the production entities. The interactions from the control mechanism towards the reputation models are given.

MULTI-AGENT MANUFACTURING CONTROL USING STIGMERGY

Abstract This paper discusses a multi-agent coordination and control system design, inspired by the behaviour of social insects. This design makes desirable overall system behaviour emerge without exposing individual agents to the complexity and the dynamics of the overall system. This enables these individual agents to survive changes without maintenance, it allows individual agents to be re-usable across systems, and it allows having the emergent behaviour handle disturbances. The paper starts with the biological concept, stigmergy, that constitutes the basis of the coordination and control system. Next, it discusses the different steps in the development of a coordination and control system.

Multi-Agent Manufacturing Control with Bayesian Networks

Abstract Research in multi-agent manufacturing control is concerned with issues surrounding the performance of collections of specially tailored interacting agents. A major concern is the design of the decision-making mechanism that the agents employ in order to determine which actions to take to achieve their goals. In manufacturing systems, the rational base for these decisions is often uncertain information. To address this problem a Bayesian network is proposed to model the schedule of successive operations. Due-dates, operation time and contracts between order and resource agents are considered as random variables. Standard computations with this Bayesian network allow the estimation of due-dates and explanatory or diagnostic tasks. This helps agents to orientate and to follow their individual intentions. The decision-making mechanism is based on normative manufacturing knowledge and is used to compare and evaluate contracts based on a standard calibration commodity. Copyright ©2001 IFAC