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By James Hendler

ISBN-10: 0080499449

ISBN-13: 9780080499444

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Waldinger, R. (1977). Achieving several goals simulaneously. In Elcock, E. , editors, Machine Intelligence 8, pages 94-136. Ellis Horwood, Edinburgh. , 1990). edu Abstract Action models used in planning systems must necessarily be abstractions of reality. It is therefore natural to include estimates of ignorance and uncertainty as part of an action model. The standard approach of assigning a unique probability distribution over possible outcomes fares poorly in the presence of abstraction because many unmodeled variables are not governed by pure random chance.

In fact, the true poststate of this example cannot be exactly represented with a belief function. One method for handling the above example exactly would be to adopt a representation scheme that is even more general than belief functions — for example, a scheme capable of representing certain non-convex sets of distributions. At this point, however, it is unclear how the additional generality could be of any use in 33 34 Chrisman the context of planning and decision making. Therefore, we keep the belief function based projection, even though a small amount of information is lost.

Ellis Horwood, Edinburgh. , 1990). edu Abstract Action models used in planning systems must necessarily be abstractions of reality. It is therefore natural to include estimates of ignorance and uncertainty as part of an action model. The standard approach of assigning a unique probability distribution over possible outcomes fares poorly in the presence of abstraction because many unmodeled variables are not governed by pure random chance. A constructive interpretation of probability based on abstracted worlds is developed and suggests modeling constraints on the outcome distribution of an action rather than just a single outcome distribution.

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Artificial Intelligence Planning Systems. Proceedings of the First Conference (AIPS 92) by James Hendler


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