An artificial discourse language for collaborative negotiation
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Multiagent negotiation under time constraints
Artificial Intelligence
Collaborative plans for complex group action
Artificial Intelligence
Reaching agreements through argumentation: a logical model and implementation
Artificial Intelligence
Distributed rational decision making
Multiagent systems
Formal methods in DAI: logic-based representation and reasoning
Multiagent systems
A commonsense language for reasoning about causation and rational action
Artificial Intelligence
Introspective and elaborative processes in rational agents
Annals of Mathematics and Artificial Intelligence
PRICAI '96 Proceedings from the Workshop on Intelligent Agent Systems, Theoretical and Practical Issues
Modeling Dialogues Using Argumentation
ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
A collaborative planning model of intentional structure
Computational Linguistics
Journal of Artificial Intelligence Research
Teambotica: a robotic framework for integrated teaming, tasking, networking, and control
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Task inference and distributed task management in the Centibots robotic system
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Interactive execution monitoring of agent teams
Journal of Artificial Intelligence Research
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Structured negotiation is proposed as a new method through which collaborating agents can seek consensus on the apportionment of tasks and resources. The approach draws on research in collaborative planning and human dialog understanding: agent interactions are organized in a manner that reflects the structure of a shared plan. Negotiations are incremental and interleaved with the shared planning process while communications supporting negotiations are made efficient by drawing on knowledge of a prevailing context. Agent proposals to team members are annotated with causal information that compactly expresses relationships between new proposals and the current context. Normative guidelines for proposal generation further restrict communications of ancillary information to only those fragments that represent departures from the norm. Finally, a set of interpretation rules allows agents to infer information not explicitly communicated.