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008 | 160915s2014 xxu| s |||| 0|eng d | ||
020 |
_a9781493902743 _9978-1-4939-0274-3 |
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024 | 7 |
_a10.1007/978-1-4939-0274-3 _2doi |
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035 | _ato000541447 | ||
040 |
_aSpringer _cSpringer _dRU-ToGU |
||
050 | 4 | _aQ334-342 | |
050 | 4 | _aTJ210.2-211.495 | |
072 | 7 |
_aUYQ _2bicssc |
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_aTJFM1 _2bicssc |
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072 | 7 |
_aCOM004000 _2bisacsh |
|
082 | 0 | 4 |
_a006.3 _223 |
100 | 1 |
_aParker, Austin. _eauthor. _9446675 |
|
245 | 1 | 0 |
_aData-driven Generation of Policies _helectronic resource _cby Austin Parker, Gerardo I. Simari, Amy Sliva, V.S. Subrahmanian. |
260 |
_aNew York, NY : _bSpringer New York : _bImprint: Springer, _c2014. |
||
300 |
_aX, 50 p. 15 illus. _bonline resource. |
||
336 |
_atext _btxt _2rdacontent |
||
337 |
_acomputer _bc _2rdamedia |
||
338 |
_aonline resource _bcr _2rdacarrier |
||
490 | 1 |
_aSpringerBriefs in Computer Science, _x2191-5768 |
|
505 | 0 | _aIntroduction and Related Work -- Optimal State Change Attempts -- Different Kinds of Effect Estimators -- A Comparison with Planning under Uncertainty -- Experimental Evaluation -- Conclusions. | |
520 | _aThis Springer Brief presents a basic algorithm that provides a correct solution to finding an optimal state change attempt, as well as an enhanced algorithm that is built on top of the well-known trie data structure. It explores correctness and algorithmic complexity results for both algorithms and experiments comparing their performance on both real-world and synthetic data. Topics addressed include optimal state change attempts, state change effectiveness, different kind of effect estimators, planning under uncertainty and experimental evaluation. These topics will help researchers analyze tabular data, even if the data contains states (of the world) and events (taken by an agent) whose effects are not well understood. Event DBs are omnipresent in the social sciences and may include diverse scenarios from political events and the state of a country to education-related actions and their effects on a school system. With a wide range of applications in computer science and the social sciences, the information in this Springer Brief is valuable for professionals and researchers dealing with tabular data, artificial intelligence and data mining. The applications are also useful for advanced-level students of computer science. | ||
650 | 0 |
_aComputer Science. _9155490 |
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650 | 0 |
_aDatabase management. _9566224 |
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650 | 0 |
_aData mining. _9306371 |
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650 | 0 |
_aArtificial intelligence. _9274099 |
|
650 | 1 | 4 |
_aComputer Science. _9155490 |
650 | 2 | 4 |
_aArtificial Intelligence (incl. Robotics). _9274102 |
650 | 2 | 4 |
_aData Mining and Knowledge Discovery. _9306372 |
650 | 2 | 4 |
_aDatabase Management. _9566226 |
650 | 2 | 4 |
_aProbability and Statistics in Computer Science. _9304554 |
700 | 1 |
_aSimari, Gerardo I. _eauthor. _9446676 |
|
700 | 1 |
_aSliva, Amy. _eauthor. _9414555 |
|
700 | 1 |
_aSubrahmanian, V.S. _eauthor. _9413054 |
|
710 | 2 |
_aSpringerLink (Online service) _9143950 |
|
773 | 0 | _tSpringer eBooks | |
830 | 0 |
_aSpringerBriefs in Computer Science, _9412137 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-1-4939-0274-3 |
912 | _aZDB-2-SCS | ||
999 | _c399198 |