Planification par fusions incrémentales de graphes
This work addresses distributed planning for agents that must cooperate to achieve shared goals, but it appears incremental as it builds on existing graph and CSP methods.
The paper tackles the problem of distributed planning by introducing a model that unifies planning steps and incorporates agent interactions early to reduce search costs, though no concrete performance numbers are provided.
In this paper, we introduce a generic and fresh model for distributed planning called "Distributed Planning Through Graph Merging" ({\sf DPGM}). This model unifies the different steps of the distributed planning process into a single step. Our approach is based on a planning graph structure for the agent reasoning and a CSP mechanism for the individual plan extraction and the coordination. We assume that no agent can reach the global goal alone. Therefore the agents must cooperate, {\it i.e.,} take in into account potential positive interactions between their activities to reach their common shared goal. The originality of our model consists in considering as soon as possible, {\it i.e.,} in the individual planning process, the positive and the negative interactions between agents activities in order to reduce the search cost of a global coordinated solution plan.