  Proactive decision support (PDS) helps in improving the decision making
experience of human decision makers in human-in-the-loop planning environments.
Here both the quality of the decisions and the ease of making them are
enhanced. In this regard, we propose a PDS framework, named RADAR, based on the
research in Automated Planning in AI, that aids the human decision maker with
her plan to achieve her goals by providing alerts on: whether such a plan can
succeed at all, whether there exist any resource constraints that may foil her
plan, etc. This is achieved by generating and analyzing the landmarks that must
be accomplished by any successful plan on the way to achieving the goals. Note
that, this approach also supports naturalistic decision making which is being
acknowledged as a necessary element in proactive decision support, since it
only aids the human decision maker through suggestions and alerts rather than
enforcing fixed plans or decisions. We demonstrate the utility of the proposed
framework through search-and-rescue examples in a fire-fighting domain.
