Automated planning is successfully used in some application areas for the synthesis of plans to control complex systems. Despite significant progress in the literature, scalability is still a major problem that hinders adoption of planning in a wider range of domains. In this PhD research in the area of integrative AI, the candidate will study methods for combining modern deep learning approaches with symbolic AI for the automatic adaptation of planning tools. In particular, he/she will develop algorithms to automatically specialize planners on specific domains to improve on scalability by exploiting the characteristics of the target domain extracted automatically by means of machine learning.