PLTOOL: A knowledge engineering tool for planning and learning

AI planning solves the problem of generating a correct and efficient ordered set of instantiated activities, from a knowledge base of generic actions, which when executed will transform some initial state into some desirable end-state. There is a long tradition of work in AI for developing planners which make use of heuristics which are shown to improve their performance in many real world and artificial domains. The developers of planners have chosen between two extremes when defining those heuristics. The domain-independent planners use domain-independent heuristics, which exploit information only from the “syntactic” structure of the problem space and of the search tree. Therefore, they do not need any “semantic” information from a given domain in order to guide the search. From a Knowledge Engineering (KE) perspective, the planners that use this type of heuristics have the advantage that the users of this technology need only focus on defining the domain theory and not ...

• Type: Journal
• Year: 2007
• Where: KER
• Authors: Susana Fernández, Daniel Borrajo, Raquel Fuentetaja, Juan D. Arias, Manuela M. Veloso
• Keywords: Domain-dependent Planners, Efficient Ordered Set, Heuristics, KER 2007