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.
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 paper 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. Results from experiments employing such a system in the Producer-Consumer-Transporter domain are also presented.
specification, management, conflict resolution, and enforcement To increase the assurance with which agents can be deployed in of policies within the specific contexts established by complex operational settings, we have been developing the KAoS policy organizational structures. Following a description of these and domain services. In conjunction with Nomads strong mobility capabilities (section 2), we will conclude with a brief summary of and safe execution features, KAoS services and tools allow for the current applications (section 3) and a brief outline of future specification, management, conflict resolution, and enforcement directions (section 4). of DAML-based policies within the specific contexts established by complex organizational structures. In this paper, we will KAoS AND NOMADS POLICY AND discuss results, issues, and lessons learned in the development of
DOMAIN SERVICES these representations, tools, and services and their use in militaryKAoS is a collection of componentized agent services compatible and space applications with several popular agent frameworks, including Nomads [27], the DARPA CoABS Grid [18], the DARPA ALP/Ultra*Log
Abstract. Exploring agent conversation in the context of fine-grained agent coordination research has raised several intellectual questions. The major issues pertain to interactions between different agent conversations, the representations chosen for different classes of conversations, the explicit modeling of interactions between the conversations, and how to address these interactions. This paper is not so ambitious as to attempt to address these questions, only frame them in the context of quantified, scheduling-centric multi-agent coordination research.
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