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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Songsak Sriboonchitta | en_US |
| dc.contributor.author | Vladik Kreinovich | en_US |
| dc.date.accessioned | 2018-09-05T04:26:23Z | - |
| dc.date.available | 2018-09-05T04:26:23Z | - |
| dc.date.issued | 2018-01-01 | en_US |
| dc.identifier.issn | 1860949X | en_US |
| dc.identifier.other | 2-s2.0-85037840125 | en_US |
| dc.identifier.other | 10.1007/978-3-319-70942-0_19 | en_US |
| dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85037840125&origin=inward | en_US |
| dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/58572 | - |
| dc.description.abstract | © Springer International Publishing AG 2018. In his 2014 book “Zero to One”, a software mogul Peter Thiel lists the lessons he learned from his business practice. Most of these lessons make intuitive sense, with one exception – his observation that “a bad plan is better than no plan” seems to be counterintuitive. In this paper, we provide a possible theoretical explanation for this somewhat counterintuitive empirical observation. | en_US |
| dc.subject | Computer Science | en_US |
| dc.title | A bad plan is better than no plan: A theoretical justification of an empirical observation | en_US |
| dc.type | Book Series | en_US |
| article.title.sourcetitle | Studies in Computational Intelligence | en_US |
| article.volume | 753 | en_US |
| article.stream.affiliations | Chiang Mai University | en_US |
| article.stream.affiliations | University of Texas at El Paso | en_US |
| Appears in Collections: | CMUL: Journal Articles | |
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