A network representation and algorithm for task planning

Abstract: "An activity planning algorithm based on a network representations of conditions and actions is presented. The algorithm performs backward expansions on each desired condition in order to express them as a combination of initial conditions and actions. A global problem network of actions and conditions is used to represent the history of successful condition expansions. This representation maintains consistency and improves the efficiency of the search procedure. Interpretation of this problem network leads to an actions network from which feasible plans are directly obtained. The network algorithm was implemented in LISP and is applied here to solve blockworld problems similar to those found in the artificial intelligence planning literature. However, the algorithm and the network representation are general and intended to be used as an analytical tool in planning systems that formulate sequences of multiple actions."