By Scot Anderson, Peter Revesz (auth.), Jean-Daniel Zucker, Lorenza Saitta (eds.)
This publication constitutes the refereed lawsuits of the sixth overseas Symposium on Abstraction, Reformulation, and Approximation, SARA 2005, held in Airth fort, Scotland, united kingdom in July 2005.
The 17 revised complete papers and eight prolonged abstracts have been conscientiously reviewed and chosen for inclusion within the booklet. additionally incorporated are three invited papers and eight examine summaries. All present features of abstraction, reformulation, and approximation within the context of human common sense reasoning, challenge fixing, and successfully reasoning in complicated domain names are addressed. one of the program fields of those innovations are computerized programming, constraint delight, layout, analysis, computer studying, seek, making plans, reasoning, video game taking part in, scheduling, and theorem proving.
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Additional info for Abstraction, Reformulation and Approximation: 6th International Symposium, SARA 2005, Airth Castle, Scotland, UK, July 26-29, 2005. Proceedings
A planning problem in the navigation domain consists in moving a mobile robot, equipped with an arm, from one location to another. The diﬀerent locations are connected by doors that can be open or closed. The blocks domain is the standard AI planning bench mark domain used to form towers of blocks according to a set of constraints over the positions of the blocks. In our experiment, it is the mobile robot that is responsible of forming the towers of blocks. Furthermore, a block is constrained to be at a speciﬁc location.
16. B. W. Wah and Y. Chen. Partitioning of temporal planning problems in mixed space using the theory of extended saddle points. In 15th IEEE International Conference on Tools with Artiﬁcial Intelligence (ICTAI 2003), pages 266–273, 2003. 17. D. E. Wilkins. Practical Planning: extending the classical AI paradigm. Morgan Kaufmann, 1988. uk Abstract. This paper describes a method for constructing and evaluating teleo-reactive policies for one or more agents, based upon discountedreward evaluation of policy-restricted subgraphs of complete situationgraphs.
The highest savings occur when abstraction step of 10 is used. In contrast, in the case of one resource the highest savings occur when the abstraction step of 40 is used. 6 Conclusions states We have shown that admissible heuristics can be generated using abstraction in stochastic domains. The results are very similar to those obtained by Holte et al. in deterministic settings . In general, the use of abstraction in both stochastic and deterministic settings is beneficial. The actual amount of savings depends on the abstraction step.