Action reversibility in planning deals with the question whether the consequences of a given action can be undone so that the state of the environment returns to what it was before the action was applied. This problem is known to be PSPACE-complete in general. In this paper, we evaluate two PSPACE-complete logic programming languages, namely: Quantified Answer Set Programming (QASP) that extends Answer Set Programming (ASP) with quantified atoms; and Bule, a logic programming language that extends Quantified Boolean Formulas (QBFs) with Datalog-like rules in order to separate the problem domain and problem instance. We give two novel encodings for the problem of action reversibility and perform experiments to see how the solvers for these two languages compare to established methods.