Data-driven Generation of Policies (SpringerBriefs in by Austin Parker,Gerardo I. Simari,Amy Sliva,V.S. Subrahmanian PDF

By Austin Parker,Gerardo I. Simari,Amy Sliva,V.S. Subrahmanian

ISBN-10: 1493902733

ISBN-13: 9781493902736

This Springer short provides a simple set of rules that gives an accurate approach to discovering an optimum kingdom swap try out, in addition to an stronger set of rules that's equipped on best of the well known trie info constitution. It explores correctness and algorithmic complexity effects for either algorithms and experiments evaluating their functionality on either real-world and artificial information. issues addressed comprise optimum nation switch makes an attempt, kingdom swap effectiveness, diversified type of influence estimators, making plans less than uncertainty and experimental overview. those issues may help researchers learn tabular info, no matter if the knowledge includes states (of the area) and occasions (taken through an agent) whose results are usually not good understood. occasion DBs are omnipresent within the social sciences and should contain different situations from political occasions and the kingdom of a rustic to education-related activities and their results on a college process. With quite a lot of functions in computing device technological know-how and the social sciences, the data during this Springer short is effective for execs and researchers facing tabular information, synthetic intelligence and knowledge mining. The functions also are valuable for advanced-level scholars of computing device science.

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Data-driven Generation of Policies (SpringerBriefs in Computer Science) by Austin Parker,Gerardo I. Simari,Amy Sliva,V.S. Subrahmanian

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