Active search in intensionally specified structured spaces

Oglic, Dino and Garnett, Roman and Gärtner, Thomas (2017) Active search in intensionally specified structured spaces. In: Thirty-First AAAI Conference (AAAI 17), 4-9 Feb 2017, San Francisco, USA.

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Abstract

We consider an active search problem in intensionally specified structured spaces. The ultimate goal in this setting is to discover structures from structurally different partitions of a fixed but unknown target class. An example of such a process is that of computer-aided de novo drug design. In the past 20 years several Monte Carlo search heuristics have been developed for this process. Motivated by these hand-crafted search heuristics, we devise a Metropolis--Hastings sampling scheme where the acceptance probability is given by a probabilistic surrogate of the target property, modeled with a max entropy conditional model. The surrogate model is updated in each iteration upon the evaluation of a selected structure. The proposed approach is consistent and the empirical evidence indicates that it achieves a large structural variety of discovered targets.

Item Type: Conference or Workshop Item (Paper)
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Depositing User: Oglic, Dino
Date Deposited: 05 Dec 2016 13:13
Last Modified: 15 Oct 2017 12:49
URI: http://eprints.nottingham.ac.uk/id/eprint/39140

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