  In this paper we present an early Apprenticeship Learning approach to mimic
the behaviour of different players in a short adaption of the interactive
fiction Anchorhead. Our motivation is the need to understand and simulate
player behaviour to create systems to aid the design and personalisation of
Interactive Narratives (INs). INs are partially observable for the players and
their goals are dynamic as a result. We used Receding Horizon IRL (RHIRL) to
learn players' goals in the form of reward functions, and derive policies to
imitate their behaviour. Our preliminary results suggest that RHIRL is able to
learn action sequences to complete a game, and provided insights towards
generating behaviour more similar to specific players.
