Merging Separately Generated Plans with Restricted Interactions

Generating action sequences to achieve a set of goals is a computationally di cult task. When multiple goals are present, the problem is even worse. Although many solutions to this problem have been discussed in the literature, practical solutions focus on the use of restricted mechanisms for planning or the application of domain dependent heuristics for providing rapid solutions (i.e. domain-dependent planning). One previously proposed technique for handling multiple goals e ciently is to design a planner or even a set of planners (usually domain-dependent) that can be used to generate separate plans for each goal. The outputs are typically either restricted to be independent and then concatenated into a single global plan, or else they are merged together using complex heuristic techniques. In this paper we explore a set of limitations, less restrictive than the assumption of independence, that still allow for the e cient merging of separate plans using straightforward algorithmic techniques. In particular, we demonstrate that for cases where separate plans can be individually generated, we can de ne a set of limitations on the allowable interactions between goals that allow e cient plan merging to occur. We propose a set of restrictions that are satis ed across a signi cant class of planning domains. We present algorithms that are e cient for special cases of multiple plan merging, propose a heuristic search algorithm that performs well in a more general case (where alternative partially-ordered plans have been generated for each goal), and describe an empirical study that demonstrates the e ciency of this search algorithm.