  Multi-agent planning (MAP) approaches are typically oriented at solving
loosely-coupled problems, being ineffective to deal with more complex,
strongly-related problems. In most cases, agents work under complete
information, building complete knowledge bases. The present article introduces
a general-purpose MAP framework designed to tackle problems of any coupling
levels under incomplete information. Agents in our MAP model are partially
unaware of the information managed by the rest of agents and share only the
critical information that affects other agents, thus maintaining a distributed
vision of the task.
