This paper describes and discusses a novel design and a prototype implementation for manufacturing control systems, aimed at handling changes and disturbances. This novel design utilizes the concept of a multi-agent system. Agents in this system use an indirect coordination mechanism, called stigmergy. Stigmergy is a class of mechanisms that mediate animal-animal interactions. It consists of in...

Enterprises face stiff competition and the pressure to improve efficiency and productivity. Since the cost of production could be reduced in the last years, further reductions can be obtained e.g. by spreading production processes over organizational boundaries to use the key competencies of the involved organizations. This shift increases the number of external links and transactions of enterp...

Many challenges in multi-agent coordination can be modeled as distributed constraint optimization problems (DCOPs) but complete algorithms do not scale well nor respond effectively to dynamic or anytime environments. We introduce a transformation of DCOPs into graphical games that allows us to devise and analyze algorithms based on local utility and prove the monotonicity property of a class of...

In crowded multi-agent navigation environments, the motion of the agents is significantly constrained by the motion of the nearby agents. This makes planning paths very difficult and leads to inefficient global motion. To address this problem, we propose a new distributed approach to coordinate the motions of agents in crowded environments. With our approach, agents take into account the veloci...

Faculty of Engineering Science and Maths School of Electronics and Computer Science Doctor of Philosophy Bayesian learning for agent coordination by Mair Allen-Williams Multi-agent systems draw together a number of significant trends in modern technology: ubiquity, decentralisation, openness, dynamism and uncertainty. As work in these fields develops, such systems face increasing challenges. Tw...

One of the major interests of Multi-Agent Systems (MAS), which are able to handle distributed planning, is coordination. This coordination requires both an adequate plan representation and eecient interacting methods between agents. Interactions are based on information exchange (e.g. data, partial or global plan) and allow agents to update their own plans by including the exchanged information...

This paper describes the initial development of an intelligent tasking model which has been designed to enable complex systems, human agents and software agents, to be tasked and controlled within a reactive workflow management paradigm. The task models exploits recent advances within the AI community in reactive control, scheduling and continuous execution. The Dynamic Execution Order Schedule...

Incorporating coalition formation algorithms into agent systems shall be advantageous due to the consequent increase in the overall quality of task performance. Coalition formation was addressed in game theory, however the game theoretic approach is centralized and computationally intractable. Recent work in DAI has resulted in distributed algorithms with computational tractability. This paper ...

In a distributed algorithm, multiple processes, or agents, work toward a common goal. More often than not, the actions of some agents are dependent on the previous execution (if not also on the outcome) of the actions of other agents. The resulting interdependencies between the timings of the actions of the various agents give rise to the study of methods for timely coordination of these action...

Auctions are promising decentralized methods for teams of agents to allocate and re-allocate tasks among themselves in dynamic, partially known and time-constrained domains with positive or negative synergies among tasks. Auctionbased coordination systems are easy to understand, simple to implement and broadly applicable. They promise to be efficient both in communication (since agents communic...