In this paper we present the syntax and semantics of a temporal action language named Alan, which was designed to model interactive multimedia presentations where the Markov property does not always hold. In general, Alan allows the specification of systems where the future state of the world depends not only on the current state, but also on the past states of the world. To the best of our knowledge, Alan is the first action language which incorporates causality with temporal formulas. (...) In the process of defining the effect of actions we define the closure with respect to a path rather than to a state, and show that the non-Markovian model is an extension of the traditional Markovian model. Finally, we establish relationship between theories of Alan and logic programs. (shrink)

The first step in reasoning about actions and change involves reasoning about how the world would evolve if a certain action is executed in a certain state. Most research on this assumes the evolution to be only a single step and focus on formulating the transition function that defines changes between states due to actions. In this paper we consider cases where the evolution is more than just a single change between one state and another. This is manifested when the (...) execution of an action may trigger execution of other actions, or when multiple agents act on the environment following certain strategies. (shrink)