0386716 20240103201909.320130111235959.9 978-3-642-24646-3 1868-4394 84885609056 10.1007/978-3-642-24647-0 Berlin Springer-Verlag 2012 194 s. P Intelligent Systems Reference Library 28 decision making Bayesian decision making rationality cav_un_auth*0101092 Guy Tatiana Valentine Adaptivní systémy Department of Adaptive Systems AS AS UTIA-B Department of Adaptive Systems Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101124 Kárný Miroslav Adaptivní systémy Department of Adaptive Systems AS AS UTIA-B Department of Adaptive Systems Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0287657 Wolpert D. H. US GA102/08/0567 GA ČR cav_un_auth*0239566 CEZ:AV0Z1075907 Prescriptive Bayesian decision making has reached its maturity and is supported by efficient, theoretically well-founded algorithms. However, experimental data shows that real decision makers choose such Bayes-optimal decisions surprisingly infrequently, often making decisions that are badly sub-optimal. So prevalent is such imperfect decision making that it should be accepted as an inherent feature of real decision makers living within interacting societies. Such societies have been investigated from an economic and game-theoretic perspective but little work has been done from the perspective of computer science, machine learning, information theory and neuroscience. The workshop Decision Making with Multiple Imperfect Decision Makers, held after the 24th Annual Conference on Neural Information Processing Systems (NIPS 2010) was a step in bringing such alternative viewpoints to bear on the topic of understanding societies of imperfect decision makers. 2013 BB 3 4 A 4a 4a 4a 20231122135432.7 RVO:67985556 http://hdl.handle.net/11104/0216152 2012 Soubory v repozitáři: Guy-0386716-3.pdf, Guy-0386716-2.pdf, Guy-0386716-1.pdf 2012 Berlin Springer-Verlag 978-3-642-24646-3 84885609056 SCOPUS