Nathaniel G. Martin and James F. Allen, "Statistical Probabilities for Planning," Technical Report 474, Department of Computer Science, University of Rochester, Rochester, NY, November 1993. Home/Search Document Details and Download
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Using Simulation-based Projection to Plan in an Uncertain and.. - Yampratoom (1994) (6 citations) (Correct)
....be used by a planner, the interface is clear enough that a human user should also be able to easily interact with it. Thus the projection module should also be integrated to the new trains World general and graphical interface as described in [Martin and Mitchell, 1994] Martin and Allen, 1991; Martin and Allen, 1993; Martin, 1993] present a language for planning with statistics. Among other things, they show how to compute confidence intervals from statistics on events. This work will provide many examples and ideas to be included in the projection module abstraction layer. Appendix A The TRAINS ....
....the interface is clear enough that a human user should also be able to easily interact with it. Thus the projection module should also be integrated to the new trains World general and graphical interface as described in [Martin and Mitchell, 1994] Martin and Allen, 1991; Martin and Allen, 1993; Martin, 1993] present a language for planning with statistics. Among other things, they show how to compute confidence intervals from statistics on events. This work will provide many examples and ideas to be included in the projection module abstraction layer. Appendix A The TRAINS Predictor User Guide ....
Nathaniel G. Martin and James F. Allen, "Statistical Probabilities for Planning," Technical Report 474, Department of Computer Science, University of Rochester, Rochester, NY, 1993.
Actions and Events in Interval Temporal Logic - Allen, Ferguson (1994) (60 citations) Self-citation (Allen) (Correct)
....evaluation should be based on how likely the assumptions are to hold. This is another motivation for favoring the explanation closure technique. It makes the assumptions that are made explicit, and thus potentially available for probabilistic analysis. Some initial work on this is described in [Martin, 1993; Martin and Allen, 1993] It is much more difficult to see how techniques that build the assumptions into the semantic model could be extended to support probabilistic reasoning. Finally, it needs to be acknowledged that formalizing knowledge using the more expressive temporal representation ....
....should be based on how likely the assumptions are to hold. This is another motivation for favoring the explanation closure technique. It makes the assumptions that are made explicit, and thus potentially available for probabilistic analysis. Some initial work on this is described in [Martin, 1993; Martin and Allen, 1993] It is much more difficult to see how techniques that build the assumptions into the semantic model could be extended to support probabilistic reasoning. Finally, it needs to be acknowledged that formalizing knowledge using the more expressive temporal representation can be difficult. Subtle ....
Nathaniel G. Martin and James F. Allen, "Statistical Probabilities for Planning," Technical Report 474, Department of Computer Science, University of Rochester, Rochester, NY, November 1993.
Knowledge Representation and Reasoning for.. - George Montague Ferguson (1995) (6 citations) Self-citation (Allen) (Correct)
....evaluation should be based on how likely the assumptions are to hold. This is another motivation for favoring the explanation closure technique. It makes the assumptions that are made explicit, and thus potentially available for probabilistic analysis. Some initial work on this is described in [Martin, 1993; Martin and Allen, 1993] It is much more difficult to see how techniques that build the assumptions into the semantic model could be extended to support probabilistic reasoning. Finally, it needs to be acknowledged that formalizing knowledge using the more expressive temporal representation can ....
....should be based on how likely the assumptions are to hold. This is another motivation for favoring the explanation closure technique. It makes the assumptions that are made explicit, and thus potentially available for probabilistic analysis. Some initial work on this is described in [Martin, 1993; Martin and Allen, 1993] It is much more difficult to see how techniques that build the assumptions into the semantic model could be extended to support probabilistic reasoning. Finally, it needs to be acknowledged that formalizing knowledge using the more expressive temporal representation can be difficult. Subtle ....
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Nathaniel G. Martin and James F. Allen, "Statistical Probabilities for Planning," Technical Report 474, Department of Computer Science, University of Rochester, Rochester, NY, November 1993.
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