By Patrick Cousot (auth.), Berthe Y. Choueiry, Toby Walsh (eds.)
This quantity includes the court cases of SARA 2000, the fourth Symposium on Abstraction, Reformulations, and Approximation (SARA). The convention was once held at Horseshoe Bay lodge and convention membership, Lake LBJ, Texas, July 26– 29, 2000, simply sooner than the AAAI 2000 convention in Austin. prior SARA meetings happened at Jackson gap in Wyoming (1994), Ville d’Est´erel in Qu´ebec (1995), and Asilomar in California (1998). The symposium grewout of a chain of workshops on abstraction, approximation, and reformulation that had taken position along AAAI on account that 1989. This year’s symposium used to be really scheduled to happen at Lago Vista golf equipment & inn on Lake Travis yet, end result of the resort’s failure to pay taxes, the convention needed to be moved past due within the day. This mischance engendered eleventh-hour reformulations, abstractions, and source re-allocations of its personal. Such are the perils of organizing a convention. this is often the ?rst SARA for which the lawsuits were released within the LNAI sequence of Springer-Verlag. we are hoping that it is a re?ection of the elevated adulthood of the ?eld and that the elevated visibility introduced through the booklet of this quantity can help the self-discipline develop even additional. Abstractions, reformulations, and approximations (AR&A) have chanced on - plications in quite a few disciplines and difficulties together with computerized progr- ming, constraint pride, layout, analysis, laptop studying, making plans, qu- itative reasoning, scheduling, source allocation, and theorem proving. The - pers during this quantity catch a cross-section of those program domains.
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Extra info for Abstraction, Reformulation, and Approximation: 4th International Symposium, SARA 2000 Horseshoe Bay, USA, July 26–29, 2000 Proceedings
Suppose that there are two deﬁned subtasks: exit from the room on the left (which terminates when the agent leaves the room by either door), and go to the goal in the room on the right. The recursively optimal policy for the left room is to leave by the nearest door. But this is not the hierarchically optimal policy for the shaded An Overview of MAXQ Hierarchical Reinforcement Learning 41 squares. For these squares, it is better to move upward and exit by the upper door. To discover this hierarchically optimal policy, information about the distance to the goal after the agent leaves the room must be propagated “into” the room (as it would be in ﬂat Q learning, for example).
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Vardi, editors, Proceedings of the Tenth International Conference on Computer Aided Verification, CAV ’98, Vancouver, British Columbia, Canada, Lecture Notes in Computer Science 1427, pages 195–206. Springer-Verlag, Berlin, Germany, June /July 1998. Y. Kesten and A. Pnueli. Modularization and abstraction: The keys to formal veriﬁcation. In L. Brim, J. Gruska, and J. Zlatuska, editors, Twentythird International Symposium on Mathematical Foundations of Computer Science 1998, Lecture Notes in Computer Science 1450, pages 54–71.
Abstraction, Reformulation, and Approximation: 4th International Symposium, SARA 2000 Horseshoe Bay, USA, July 26–29, 2000 Proceedings by Patrick Cousot (auth.), Berthe Y. Choueiry, Toby Walsh (eds.)
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