A novel distributed dynamic planning approach based on constraint satisfaction

Abstract

In this work, we propose a new distributed dynamic planning approach based on constraint satisfaction, able to take into account the satisfaction of the constraints in all new versions of generated plans. Our approach is to generate, a new plan by each agent, whenever there is a change in its set of actions to plan caused by the unpredictable changes of the environment. This does not alter the satisfaction of the constraints taken into account during the generation of the initial plan. Our approach allows the integration of all the new actions, generated by the changes, in the new plan at the right place, which preserves the satisfaction of the constraints. For this, the approach uses genetic algorithm where the fitness function is defined on the basis of the constraints to be satisfied. The proposed approach is supported by a formal framework and applied on a concrete case study to illustrate and show its usefulness.