The specific organization used by a multi-agent system is crucial for its effectiveness and efficiency. In dynamic environments, or when the objectives of the system shift, the organization must therefore be able to change as well. In this abstract we propose using a general diagnosis engine to drive this process of adaptation, using the TAEMS modeling language as the primary representation of organizational information. A complete version of this paper is at [1] . As the sizes of multi-agent systems grow in the number of their participants, the organization of those agents will be increasingly important. In such an environment, an organization is used to limit the range of control decisions agents must make, which is a necessary component of scalable systems. Are agent agents arranged in clusters, a hierarchy, a graph, or some other type of organization? Are the agents' activities or behaviors driven solely by local concerns, or do external peers or managers have direct influence as well? Is communication between agents active, via messaging of some sort, or passive, using observations or engineered assumptions? These and other characteristics define the organizational structure of a multi-agent systemthe rules which define the roles agents play and the manners in which they interact with other agents in the system. Clearly the characteristics described above will have an impact on the efficiency and responsiveness of both large and small multi-agent systems. It should also be intuitively clear that the effectiveness of the organization is dependent on the agents, environment, and goals involved in the system. The problem then, is how to derive and maintain such a structure given a particular situation. The term Organizational Self-Design (OSD) has been used previously to describe the general technique of employing the members of a multi-agent system to generate or adapt their own organizational structures at runtime. Earlier work in this area tended to focus on adapting specific qualities of the organization, such as task allocation or load balancing. Organizational structure generation has also been proposed as arising from local, global, and hybrid perspectives. In this abstract we outline a more general approach, using diagnosis, to detect deficiencies in the organizational model and assist in the creation of solutions to those deficiencies; the eventual goal being to create a reusable organizational adaptation engine. We will show how a general diagnosis engine, coupled with a powerful representation of that organization, can be used to effect change in a wide range of characteristics. In the architecture we propose, critical components within the agent, such as those responsible for problem solving, negotiation and scheduling, obtain the vast majority of their information from an organizational design layer. This layer abstracts and filters elements of the operating environment in a manner consistent with the agent's role in the organization. The abstraction is composed of one or more information sources, such as TAEMS structures, capable of encoding the various aspects of the organization. To permit adaptation, the organizational design layer is maintained by a diagnostic subsystem, which attempts to repair faults and inefficiencies by adjusting elements of the organizational structure. This diagnostics process can itself be driven by a number of sources, including observations of the environment, conditions monitored within the agent, and discourse with other agents. The direct effects of these diagnoses will typically (but not necessarily) take place within a relatively small group of agents, so one can think of this technique as a search for the correct organization through local adaptation. The range of information that comprises an organizational structure can be quite broad. It is our opinion that there is no single, comprehensive set of characteristics that 0-7695-0625-9/00 $10.00 ã 2000 IEEE
In a similar work, Kamboj et al. REF focus on organizational structure adaptation based on two primitives: spawning (creation of a new agent) and composition (merging several agents).
Using self-diagnosis to adapt organizational structures
Proceedings Fourth International Conference on MultiAgent Systems
Proceedings Fourth International Conference on MultiAgent Systems
Engineering Computer Science