Distributed data structures in Linda
POPL '86 Proceedings of the 13th ACM SIGACT-SIGPLAN symposium on Principles of programming languages
Analysis of Symbolic Data: Exploratory Methods for Extracting Statistical Information from Complex Data
Computer Supported Cooperative Work
Semantics of Agent Communication Languages for Group Interaction
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
First steps towards multi-party communication
AC'04 Proceedings of the 2004 international conference on Agent Communication
On the Use of Symbolic Data Analysis to Model Communication Environments
CIA '08 Proceedings of the 12th international workshop on Cooperative Information Agents XII
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Two-party communication is the most-studied model to support interaction between two cognitive agents, whereas that is only one case of what an agent should be able to do. Multi-party communications enhance this model, by taking into account all the roles an agent can have in a communication. Nevertheless, there are no generic models and infrastructures that enable to apply multi-party communication in a standardized way. We emphasize that the environment, in the sense of a common medium for the agents, is a suitable paradigm to support multi-party communication. We propose a general and operational model called Environment as Active Support of Interaction (EASI), that enables each agent to actively modify the environment according to its communication needs. Algorithms are proposed and assessed with an example stemming from the ambient intelligence domain.