CAPIR: Collaborative Action Planning with Intention Recognition
  We apply decision theoretic techniques to construct non-player characters
that are able to assist a human player in collaborative games. The method is
based on solving Markov decision processes, which can be difficult when the
game state is described by many variables. To scale to more complex games, the
method allows decomposition of a game task into subtasks, each of which can be
modelled by a Markov decision process. Intention recognition is used to infer
the subtask that the human is currently performing, allowing the helper to
assist the human in performing the correct task. Experiments show that the
method can be effective, giving near-human level performance in helping a human
in a collaborative game.
