Titlebook: Data-driven Generation of Policies; Austin Parker,Gerardo I. Simari,V.S. Subrahmanian Book 2014 The Author(s) 2014 Automatic policy genera

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Different Kinds of Effect Estimators,. An effect estimator essentially answers the question: “if I succeed in changing the environment in this way, what is the probability that the environment satisfies my goal?”. We also present the . algorithm, an optimized approach to computingoptimal state change attempts when using a special kind of effect estimator.

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A Comparison with Planning Under Uncertainty,y, in this chapter we will propose and discuss a mapping between an instance of an OSCA problem and an instance of a .. The ultimate goal is to show that optimal state change attempt problems can indeed be solved by applying techniques from the planning under uncertainty literature, but this approach will be ultimately impractical.

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Gary A. Maddux,William E. Soudere, will change the action attributes with the hope that these changes will result in a change in the state. For instance, considering the school data described in the previous chapter, SCAs represent policies Policy designed with a certain goal in mind; we provide an example in which a change in the

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https://doi.org/10.1007/978-1-4615-3062-6. An effect estimator essentially answers the question: “if I succeed in changing the environment in this way, what is the probability that the environment satisfies my goal?”. We also present the . algorithm, an optimized approach to computingoptimal state change attempts when using a special kind

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https://doi.org/10.1007/978-94-011-1298-7y, in this chapter we will propose and discuss a mapping between an instance of an OSCA problem and an instance of a .. The ultimate goal is to show that optimal state change attempt problems can indeed be solved by applying techniques from the planning under uncertainty literature, but this approac

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Austin Parker,Gerardo I. Simari,V.S. SubrahmanianIncludes supplementary material:

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