Domain-independent planning: representation and plan generation
Artificial Intelligence
Planning as search: a quantitative approach
Artificial Intelligence
Reasoning About Theory Adequacy. A New Solution To The Qualification Problem
Fundamenta Informaticae
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This paper describes the localized search mechanism of the GEMPLAN multiagent planner. Both formal complexity results and empirical results are provided, demonstrating the benefits of localized search, A localized domain description is one that decomposes domain activities and requirements into a set of regions. This description is used to infer how domain requirements are semantically localized and, as a result, to enable the decomposition of the planning search space into a set of spaces, one for each domain region. Benefits of localization include a smaller and cheaper overall search space as well as heuristic guidance in controlling search. Such benefits are critical if current planning technologies and other types of reasoning are to be scaled up to large, complex domains.