Incremental Heuristic Search in AI

Incremental search reuses information from previous searches to find solutions to a series of similar search problems potentially faster than is possible by solving each search problem from scratch. This is important because many AI systems have to adapt their plans continuously to changes in (their knowledge of) the world. AI has developed several ways of speeding up searches by trading off the search time and the cost of the resulting path, which includes using inadmissible heuristics (Pohl 1973, 1970) and search with limited look ahead (Korf 1990; Ishida and Korf 1991; Koenig 2001), which is also called real-time or agent-centered search. In this article, we discuss a different way of speeding up searches, namely, incremental search. Incremental search is a search technique for continual planning (or, synonymously, replanning, plan reuse, and lifelong planning) that reuses information from previous searches to find solutions to a series of similar search problems potentially faster than is possible by solving each search problem from scratch.