Real-time heuristic search algorithms are suitable for situated agents that
need to make their decisions in constant time. Since the original work by Korf
nearly two decades ago, numerous extensions have been suggested. One of the
most intriguing extensions is the idea of backtracking wherein the agent
decides to return to a previously visited state as opposed to moving forward
greedily. This idea has been empirically shown to have a significant impact on
various performance measures.