One major problem in the process of knowledge assimilation is how to deal with inconsistency of new knowledge and the existing knowledge base. In this paper we present a formal, provably correct and yet computational methodology for assimilation of new knowledge into knowledge bases about actions and changes based on the slogan: what is believed is what is explained. Technically, we employ Gelfond and Lifschitz' action description language A to describe domains of actions. The knowledge bases on domains of actions are defined and obtained by a new translation from domain descriptions in A into abductive normal logic programs, where a time dimension is incorporated. The knowledge bases are shown to be both sound and complete with respect to their domain descriptions. In particular, we propose a possible causes approach (PCA) to knowledge assimilation about evolving domains of actions, in contrast to Ginsberg's possible worlds approach (PWA) and Winslett's possible models approach (PMA). A possible cause of new knowledge consists of abduced occurrences of actions and value propositions about the initial state of the domain of actions, that would allow to derive the new knowledge. We show how to compute possible causes with abductive logic programming, and present some techniques to improve search efficiency. We use examples to compare our possible causes approach with syntax-based approaches, such as Ginsberg's possible worlds approach, and semantics-based approaches, such as Winslett's possible models approach, to belief revision/update.