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Additional resources for Engineering Self-Organising Systems: 4th International Workshop, ESOA 2006, Hakodate, Japan, May 9, 2006, Revised and Invited Papers
However this decription is only used in the Service Matchmaking process and not used during the analysis nor the modelling phases. These aspects are tackled in our approach with the notion of capacity as a basic decription of an agent know-how. To distinguish the agent from its competences,  and  have introduced the notion of skill to describe basic agent abilities and allowing the deﬁnition of an atomic agent, that can dynamically evolve by learning/acquiring new skills. Then [1,2] have extended this approach to integrate this notion of skill as a basic building block for role speciﬁcation.
Not exploiting a piece of coordination information, could possibly lead to greater advantages in the future. However, it is a general drawback of distributed solutions, where the possibility of globally informed decisions by distributed agents is often ruled out due to the need for eﬃcient and adaptive coordination . Solution Inspiration. The Gradient Field coordination mechanism takes its inspiration from physics and biology. In physics [20,19,21], the same mechanism can be found in the way masses and particles in our universe adaptively move and globally self-organise their movements accordingly to the locally perceived magnitude of gravitational/electro-magnetic/potential ﬁelds.
The coordination mechanism has to be robust and ﬂexible in the face of frequent changes. Also, local estimates of global information are the only possible way to coordinate. As such, decentralised coordination is the only possible alternative. Some locally available information is needed indicating the global usage of resources. 2 Problem/Intent – Resource Allocation: How to do eﬃcient resource allocation [26,4,10,32] in a distributed and decentralised manner? Resources can be interpreted as tasks, bandwidth, manufacturing devices, etc.