 In the field of artificial intelligence (AI), the aim is to devise intelligently behaving computer-based artifacts (with the purpose of understanding human intelligence or just making intelligent computer systems and programs). In order to achieve this, there is a tradition within AI to try and construct these systems based on symbolic representations of all relevant factors involved. This tradition is called symbolic AI or ‘good old-fashioned’ AI (GOFAI). In this tradition the sub-area of knowledge representation (KR) obviously is of major importance: it played an important role since the inception of AI, and has developed to a substantial field of its own. One of the prominent areas in KR concerns the representation of actions, performed by either the system to be devised itself or the actors in its environment. Of course, besides their pure representation also reasoning about actions is important, since representation and reasoning with these representations are deemed to be closely connected within KR (which is sometime also called KR&amp;R, knowledge representation &amp; reasoning). A related, more recent development within AI is that of basing the construction of intelligent systems on the concept of an (intelligent) agent, an autonomously acting entity, regarding which, by its very nature, logics of action play a crucial role in obtaining a logical description and specification.