SOAR: an architecture for general intelligence
Artificial Intelligence
International Journal of Man-Machine Studies - Knowledge acquisition for knowledge-based systems. Part 2
An artificial discourse language for collaborative negotiation
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Communication and cooperation in agent systems: a pragmatic theory
Communication and cooperation in agent systems: a pragmatic theory
Communicative actions for artificial agents
Software agents
Semantics and conversations for an agent communication language
Readings in agents
Designing Conversation Policies using Joint Intention Theory
ICMAS '98 Proceedings of the 3rd International Conference on Multi Agent Systems
Compiling Dynamic Agent Conversations
KI '02 Proceedings of the 25th Annual German Conference on AI: Advances in Artificial Intelligence
Normative Communication Models for Agent
Autonomous Agents and Multi-Agent Systems
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It is possible to define conversation policies, such as communication or dialogue protocols, that are based strictly on what messages and, respectively, what performatives may follow each other. While such an approach has many practical applications, such protocols support only "local coherence" in a conversation. Lengthy message exchanges require some infrastructure to lend them "global coherence." Recognition of agent intentions about the joint task is essential for this global coherence, but there are further mechanisms needed to ensure that both local and global coherence are jointly maintained. This paper presents a general yet practical approach to designing, managing, and engineering agents that can do simple run-time intention recognition without creating complex multi-state protocols. In this approach we promote developing abstract task models and designing conversation policies in terms of such models. An implemented agent assistant based on these ideas is briefly described.