It has been shown recently that the performance of greedy best-first search (GBFS) for
computing plans that are not necessarily optimal can be improved by adding forms of …

We introduce two novel tree search algorithms that use a policy to guide search. The first
algorithm is a best-first enumeration that uses a cost function that allows us to provide an …

Searching for a path between two nodes in a graph is one of the most well-studied and
fundamental problems in computer science. In numerous domains such as robotics, AI, or …

Applications that require alternative plans challenge the single solution, single quality metric
assumptions upon which many classical planners are designed and evaluated. To evaluate …

Abstract Greedy Best-First Search (GBFS) is a powerful algorithm at the heart of many state
of the art satisficing planners. One major weakness of GBFS is its behavior in so-called …

Balancing exploration and exploitation has been an important problem in both adversarial
games and automated planning. While it has been extensively analyzed in the Multi-Armed …

Successful heuristic search planners for satisficing planning like FF or LAMA are usually
based on one or more best first search techniques. Recent research has led to planners like …

Finding high quality plans for large planning problems is hard. Although some current
anytime planners are often able to improve plans quickly, they tend to reach a limit at which …

Random walks have become a popular component of recent planning systems. The
increased exploration is a valuable addition to more exploitative search methods such as …

Most of the satisficing planners which are based on heuristic search iteratively improve their
solution quality through an anytime approach. Typically, the lowest-cost solution found so far …