Planning activity needs to deal with the problem of incomplete and dynamic knowledge. In a typical real environment, knowledge has to be dynamically acquired during the computational process, while traditionai planners reason by assuming that the world is closed and static. We deal with this problem by defining the planning problem as a constraint satisfaction problem (CSP) in which variables range on partially or completely unknown domains. While typical CSPs work exclusively with completely known variable domains, in our solution, some constraints, called Interactive Constraints (IC), may result in a knowledge acquisition and a consequent propagation Knowledge acquisition can be guided by ICs in order to retrieve only consistent information for the planner. We present a hybrid approach to planning which exploits this framework both in the generative and reactive phase.