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020 ▼a 9780192585431 ▼q electronic book
020 ▼a 0192585436 ▼q electronic book
020 ▼a 9780191881589 ▼q electronic book
020 ▼a 0191881589 ▼q electronic book
020 ▼a 9780192585448 ▼q (electronic bk.)
020 ▼a 0192585444 ▼q (electronic bk.)
020 ▼z 9780198846420 ▼q print
035 ▼a 2245841 ▼b (N$T)
035 ▼a (OCoLC)1119611780
040 ▼a EBLCP ▼b eng ▼e rda ▼c EBLCP ▼d YDXIT ▼d CUS ▼d OH1 ▼d N$T ▼d 248032
049 ▼a MAIN
050 4 ▼a QA76.9.C65 ▼b R68 2019
08204 ▼a 003.3 ▼2 23
1001 ▼a Rouse, William B., ▼e author.
24510 ▼a Computing possible futures : ▼b model-based explorations of "what if?" / ▼c William B. Rouse. ▼h [electronic resource]
260 ▼a Oxford ; ▼a New York, NY : ▼b Oxford University Press, ▼c [2019]
300 ▼a 1 online resource (202 pages)
336 ▼a text ▼b txt ▼2 rdacontent
337 ▼a computer ▼b c ▼2 rdamedia
338 ▼a online resource ▼b cr ▼2 rdacarrier
520 ▼a This book discusses the use of models and interactive visualizations to explore designs of systems and policies in determining whether such designs would be effective. Executives and senior managers are very interested in what "data analytics" can do for them and, quite recently, what the prospects are for artificial intelligence and machine learning. They want to understand and then invest wisely. They are reasonably skeptical, having experienced overselling and under-delivery. They ask about reasonable and realistic expectations. Their concern is with the futurity of decisions they are currently entertaining. They cannot fully address this concern empirically. Thus, they need some way to make predictions. The problem is that one rarely can predict exactly what will happen, only what might happen. To overcome this limitation, executives can be provided predictions of possible futures and the conditions under which each scenario is likely to emerge. Models can help them to understand these possible futures. Most executives find such candor refreshing, perhaps even liberating. Their job becomes one of imagining and designing a portfolio of possible futures, assisted by interactive computational models. Understanding and managing uncertainty is central to their job. Indeed, doing this better than competitors is a hallmark of success. This book is intended to help them understand what fundamentally needs to be done, why it needs to be done, and how to do it. The hope is that readers will discuss this book and develop a "shared mental model" of computational modeling in the process, which will greatly enhance their chances of success.
588 ▼a Description based on online resource; title from digital title page (viewed on September 25, 2019).
590 ▼a Added to collection customer.56279.3
650 0 ▼a Computer simulation.
650 0 ▼a Mathematical models.
650 0 ▼a Information visualization.
650 0 ▼a Management ▼x Data processing.
650 0 ▼a Decision making.
655 4 ▼a Electronic books.
77608 ▼i Print version: ▼z 9780198846420 ▼w (OCoLC)1091587578
85640 ▼3 EBSCOhost ▼u https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=2245841
938 ▼a EBL - Ebook Library ▼b EBLB ▼n EBL5891311
938 ▼a Oxford University Press USA ▼b OUPR ▼n EDZ0002088637
938 ▼a EBSCOhost ▼b EBSC ▼n 2245841
990 ▼a 관리자
994 ▼a 92 ▼b N$T