000 03503nam a22005415i 4500
001 978-3-031-01578-6
003 DE-He213
005 20240730163631.0
007 cr nn 008mamaa
008 220601s2018 sz | s |||| 0|eng d
020 _a9783031015786
_9978-3-031-01578-6
024 7 _a10.1007/978-3-031-01578-6
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
100 1 _aRosenfeld, Ariel.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_979639
245 1 0 _aPredicting Human Decision-Making
_h[electronic resource] :
_bFrom Prediction to Action /
_cby Ariel Rosenfeld, Sarit Kraus.
250 _a1st ed. 2018.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2018.
300 _aXVI, 134 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Artificial Intelligence and Machine Learning,
_x1939-4616
505 0 _aPreface -- Acknowledgments -- Introduction -- Utility Maximization Paradigm -- Predicting Human Decision-Making -- From Human Prediction to Intelligent Agents -- Which Model Should I Use? -- Concluding Remarks -- Bibliography -- Authors' Biographies -- Index .
520 _aHuman decision-making often transcends our formal models of "rationality." Designing intelligent agents that interact proficiently with people necessitates the modeling of human behavior and the prediction of their decisions. In this book, we explore the task of automatically predicting human decision-making and its use in designing intelligent human-aware automated computer systems of varying natures-from purely conflicting interaction settings (e.g., security and games) to fully cooperative interaction settings (e.g., autonomous driving and personal robotic assistants). We explore the techniques, algorithms, and empirical methodologies for meeting the challenges that arise from the above tasks and illustrate major benefits from the use of these computational solutions in real-world application domains such as security, negotiations, argumentative interactions, voting systems, autonomous driving, and games. The book presents both the traditional and classical methods as well asthe most recent and cutting edge advances, providing the reader with a panorama of the challenges and solutions in predicting human decision-making.
650 0 _aArtificial intelligence.
_93407
650 0 _aMachine learning.
_91831
650 0 _aNeural networks (Computer science) .
_979640
650 1 4 _aArtificial Intelligence.
_93407
650 2 4 _aMachine Learning.
_91831
650 2 4 _aMathematical Models of Cognitive Processes and Neural Networks.
_932913
700 1 _aKraus, Sarit.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_979641
710 2 _aSpringerLink (Online service)
_979642
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031000232
776 0 8 _iPrinted edition:
_z9783031004506
776 0 8 _iPrinted edition:
_z9783031027062
830 0 _aSynthesis Lectures on Artificial Intelligence and Machine Learning,
_x1939-4616
_979643
856 4 0 _uhttps://doi.org/10.1007/978-3-031-01578-6
912 _aZDB-2-SXSC
942 _cEBK
999 _c84818
_d84818