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==Raghuram Ramanujan et al.==
Quote by [[Raghuram Ramanujan]], [[Ashish Sabharwal]], and [[Bart Selman]] from their abstract ''On Adversarial Search Spaces and Sampling-Based Planning'' <ref>[[Raghuram Ramanujan]], [[Ashish Sabharwal]], [[Bart Selman]] ('''2010'''). ''[http://www.aaai.org/ocs/index.php/ICAPS/ICAPS10/paper/view/1458 On Adversarial Search Spaces and Sampling-Based Planning]''. [http://www.aaai.org/Press/Proceedings/icaps10.php ICAPS 2010]</ref>:
UCT has been shown to outperform traditional [[Minimax|minimax]] based approaches in several challenging domains such as [[Go]] and [[KriegspielKriegSpiel]], although minimax search still prevails in other domains such as [[Chess]]. This work provides insights into the properties of adversarial search spaces that play a key role in the success or failure of UCT and similar sampling-based approaches. We show that certain "early loss" or "shallow trap" configurations, while unlikely in Go, occur surprisingly often in games like Chess (even in grandmaster games). We provide evidence that UCT, unlike minimax search, is unable to identify such traps in Chess and spends a great deal of time exploring much deeper game play than needed.
=See also=
