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Abstract. In this chapter, we discuss the design of adaptive hierarchical organizations for multi-agent systems (MAS). Hierarchical organizations have a number of advantages such as their ability to handle complex problems and their scalability to large organizations. By introducing adaptivity in the structure of hierarchical MAS organizations, we enable agents to balance resources in their organization. We will first provide a number of generic principles for the design of hierarchical MAS organizations. We show how these principles are used to design three different hierarchical organizations for a search and rescue task in the RoboCupRescue simulation environment. The first two of these organizations are static, and the third is able to adapt its structure. An empirical study on the performance of these three organizations shows that the dynamic organization performs better than the two static organizations.

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systems depend on the underlying model for their performance, fault coverage, cost, and brittleness. Many device models use a device's structure and behavior to simulate behavior based on local interactions between primitive components. These models are easily derived and seem to work for simple (mainly static) devices.As behavior becomes more complex, though, a more global view can provide a better insight into what a device is doing. Concepts dealing with abstractions of "raw" behavior reflect this global view. One important type of abstraction reflects a device's functions, that is, its purposes or intentions. Such a functional view of a device organizes its structure and behavior accordingly.Previous work illustrated diagnosis and design based on the functional-modeling framework' and has been applied to envisionment.* Researchers have also tried to identify generic functional primitives as the basis of a functional ~n t o l o g y .~ These approaches are mainly concerned with representing and simulating device behavior and functionality. However, functions are not the only useful behavioral abstractions for diagnosis. Since diagnosis imposes 26

Research in the area of Multi-Agent System (MAS) organization has shown that the ability for a MAS to adapt its organizational structure can be beneficial when coping with dynamics and uncertainty in the MASs environment. Different types of reorganization exist, such as changing relations and interaction patterns between agents, changing agent roles and changing the coordination style in the MAS. In this paper we propose a framework for agent Coordination and Reorganization (AgentCoRe) that incorporates each of these aspects of reorganization. We describe both declarative and procedural knowledge an agent uses to decompose and assign tasks, and to reorganize. The RoboCupRescue simulation environment is used to demonstrate how AgentCoRe is used to build a MAS that is capable of reorganizing itself by changing relations, interaction patterns and agent roles.