Active search in intensionally specified structured spaces
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 th...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
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AAAI Press
2017
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| Online Access: | https://eprints.nottingham.ac.uk/39140/ |
| _version_ | 1848795772957491200 |
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| author | Oglic, Dino Garnett, Roman Gärtner, Thomas |
| author_facet | Oglic, Dino Garnett, Roman Gärtner, Thomas |
| author_sort | Oglic, Dino |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T19:37:24Z |
| format | Conference or Workshop Item |
| id | nottingham-39140 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:37:24Z |
| publishDate | 2017 |
| publisher | AAAI Press |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-391402020-05-04T18:35:26Z https://eprints.nottingham.ac.uk/39140/ Active search in intensionally specified structured spaces Oglic, Dino Garnett, Roman Gärtner, Thomas 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. AAAI Press 2017-02-09 Conference or Workshop Item PeerReviewed Oglic, Dino, 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. http://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14952 |
| spellingShingle | Oglic, Dino Garnett, Roman Gärtner, Thomas Active search in intensionally specified structured spaces |
| title | Active search in intensionally specified structured spaces |
| title_full | Active search in intensionally specified structured spaces |
| title_fullStr | Active search in intensionally specified structured spaces |
| title_full_unstemmed | Active search in intensionally specified structured spaces |
| title_short | Active search in intensionally specified structured spaces |
| title_sort | active search in intensionally specified structured spaces |
| url | https://eprints.nottingham.ac.uk/39140/ https://eprints.nottingham.ac.uk/39140/ |