Collaborative plans for complex group action
Artificial Intelligence
Algorithms for Distributed Constraint Satisfaction: A Review
Autonomous Agents and Multi-Agent Systems
A collaborative planning model of intentional structure
Computational Linguistics
Continual planning and acting in dynamic multiagent environments
PCAR '06 Proceedings of the 2006 international symposium on Practical cognitive agents and robots
PDDL2.1: an extension to PDDL for expressing temporal planning domains
Journal of Artificial Intelligence Research
The fast downward planning system
Journal of Artificial Intelligence Research
Planning executing sensing and replanning for information gathering
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Engineering intelligent information-processing systems with CAST
Advanced Engineering Informatics
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Multiagent environments are often highly dynamic and only partially observable which makes deliberative action planning computationally hard. In many such environments, however, agents can take a more proactive approach and suspend planning for partial plan execution, especially for active information gathering and interaction with others. This paper presents a new algorithm for Continual Collaborative Planning (CCP) that enables agents to deliberately interleave planning, acting, perception and communication. Our implementation of CCP has been evaluated with MAPSIM, a tool that automatically generates multiagent simulations from formal multiagent planning (MAP) domains. For different such simulations, we show how CCP leads to collaborative planning and acting and, despite minimal linguistic capabilities, to fairly natural dialogues between agents.