Learning Robust Search Strategies Using a Bandit-Based Approach Article Swipe
Wei Xia
,
Roland H. C. Yap
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1609/aaai.v32i1.12211
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1609/aaai.v32i1.12211
Effective solving of constraint problems often requires choosing good or specific search heuristics. However, choosing or designing a good search heuristic is non-trivial and is often a manual process. In this paper, rather than manually choosing/designing search heuristics, we propose the use of bandit-based learning techniques to automatically select search heuristics. Our approach is online where the solver learns and selects from a set of heuristics during search. The goal is to obtain automatic search heuristics which give robust performance. Preliminary experiments show that our adaptive technique is more robust than the original search heuristics. It can also outperform the original heuristics.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1609/aaai.v32i1.12211
- https://ojs.aaai.org/index.php/AAAI/article/download/12211/12070
- OA Status
- diamond
- Cited By
- 21
- References
- 34
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2788273636
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2788273636Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1609/aaai.v32i1.12211Digital Object Identifier
- Title
-
Learning Robust Search Strategies Using a Bandit-Based ApproachWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2018Year of publication
- Publication date
-
2018-04-26Full publication date if available
- Authors
-
Wei Xia, Roland H. C. YapList of authors in order
- Landing page
-
https://doi.org/10.1609/aaai.v32i1.12211Publisher landing page
- PDF URL
-
https://ojs.aaai.org/index.php/AAAI/article/download/12211/12070Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://ojs.aaai.org/index.php/AAAI/article/download/12211/12070Direct OA link when available
- Concepts
-
Heuristics, Computer science, Heuristic, Set (abstract data type), Solver, Machine learning, Artificial intelligence, Process (computing), Hyper-heuristic, Mathematical optimization, Mathematics, Robot, Operating system, Programming language, Robot learning, Mobile robotTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
21Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2, 2024: 2, 2023: 1, 2022: 2, 2021: 3Per-year citation counts (last 5 years)
- References (count)
-
34Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W2788273636 |
|---|---|
| doi | https://doi.org/10.1609/aaai.v32i1.12211 |
| ids.doi | https://doi.org/10.1609/aaai.v32i1.12211 |
| ids.mag | 2788273636 |
| ids.openalex | https://openalex.org/W2788273636 |
| fwci | 5.8914956 |
| type | article |
| title | Learning Robust Search Strategies Using a Bandit-Based Approach |
| biblio.issue | 1 |
| biblio.volume | 32 |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T12101 |
| topics[0].field.id | https://openalex.org/fields/18 |
| topics[0].field.display_name | Decision Sciences |
| topics[0].score | 0.9973000288009644 |
| topics[0].domain.id | https://openalex.org/domains/2 |
| topics[0].domain.display_name | Social Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1803 |
| topics[0].subfield.display_name | Management Science and Operations Research |
| topics[0].display_name | Advanced Bandit Algorithms Research |
| topics[1].id | https://openalex.org/T12401 |
| topics[1].field.id | https://openalex.org/fields/18 |
| topics[1].field.display_name | Decision Sciences |
| topics[1].score | 0.996999979019165 |
| topics[1].domain.id | https://openalex.org/domains/2 |
| topics[1].domain.display_name | Social Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1803 |
| topics[1].subfield.display_name | Management Science and Operations Research |
| topics[1].display_name | Scheduling and Timetabling Solutions |
| topics[2].id | https://openalex.org/T10100 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.9958999752998352 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1702 |
| topics[2].subfield.display_name | Artificial Intelligence |
| topics[2].display_name | Metaheuristic Optimization Algorithms Research |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C127705205 |
| concepts[0].level | 2 |
| concepts[0].score | 0.9098223447799683 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q5748245 |
| concepts[0].display_name | Heuristics |
| concepts[1].id | https://openalex.org/C41008148 |
| concepts[1].level | 0 |
| concepts[1].score | 0.6722232699394226 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[1].display_name | Computer science |
| concepts[2].id | https://openalex.org/C173801870 |
| concepts[2].level | 2 |
| concepts[2].score | 0.5941953063011169 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q201413 |
| concepts[2].display_name | Heuristic |
| concepts[3].id | https://openalex.org/C177264268 |
| concepts[3].level | 2 |
| concepts[3].score | 0.5906800627708435 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q1514741 |
| concepts[3].display_name | Set (abstract data type) |
| concepts[4].id | https://openalex.org/C2778770139 |
| concepts[4].level | 2 |
| concepts[4].score | 0.5404421091079712 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q1966904 |
| concepts[4].display_name | Solver |
| concepts[5].id | https://openalex.org/C119857082 |
| concepts[5].level | 1 |
| concepts[5].score | 0.4762130677700043 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q2539 |
| concepts[5].display_name | Machine learning |
| concepts[6].id | https://openalex.org/C154945302 |
| concepts[6].level | 1 |
| concepts[6].score | 0.46954450011253357 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[6].display_name | Artificial intelligence |
| concepts[7].id | https://openalex.org/C98045186 |
| concepts[7].level | 2 |
| concepts[7].score | 0.4629422426223755 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q205663 |
| concepts[7].display_name | Process (computing) |
| concepts[8].id | https://openalex.org/C117270229 |
| concepts[8].level | 5 |
| concepts[8].score | 0.4287901818752289 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q5957539 |
| concepts[8].display_name | Hyper-heuristic |
| concepts[9].id | https://openalex.org/C126255220 |
| concepts[9].level | 1 |
| concepts[9].score | 0.42153671383857727 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q141495 |
| concepts[9].display_name | Mathematical optimization |
| concepts[10].id | https://openalex.org/C33923547 |
| concepts[10].level | 0 |
| concepts[10].score | 0.17196449637413025 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[10].display_name | Mathematics |
| concepts[11].id | https://openalex.org/C90509273 |
| concepts[11].level | 2 |
| concepts[11].score | 0.0 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q11012 |
| concepts[11].display_name | Robot |
| concepts[12].id | https://openalex.org/C111919701 |
| concepts[12].level | 1 |
| concepts[12].score | 0.0 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q9135 |
| concepts[12].display_name | Operating system |
| concepts[13].id | https://openalex.org/C199360897 |
| concepts[13].level | 1 |
| concepts[13].score | 0.0 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q9143 |
| concepts[13].display_name | Programming language |
| concepts[14].id | https://openalex.org/C188888258 |
| concepts[14].level | 4 |
| concepts[14].score | 0.0 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q7353390 |
| concepts[14].display_name | Robot learning |
| concepts[15].id | https://openalex.org/C19966478 |
| concepts[15].level | 3 |
| concepts[15].score | 0.0 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q4810574 |
| concepts[15].display_name | Mobile robot |
| keywords[0].id | https://openalex.org/keywords/heuristics |
| keywords[0].score | 0.9098223447799683 |
| keywords[0].display_name | Heuristics |
| keywords[1].id | https://openalex.org/keywords/computer-science |
| keywords[1].score | 0.6722232699394226 |
| keywords[1].display_name | Computer science |
| keywords[2].id | https://openalex.org/keywords/heuristic |
| keywords[2].score | 0.5941953063011169 |
| keywords[2].display_name | Heuristic |
| keywords[3].id | https://openalex.org/keywords/set |
| keywords[3].score | 0.5906800627708435 |
| keywords[3].display_name | Set (abstract data type) |
| keywords[4].id | https://openalex.org/keywords/solver |
| keywords[4].score | 0.5404421091079712 |
| keywords[4].display_name | Solver |
| keywords[5].id | https://openalex.org/keywords/machine-learning |
| keywords[5].score | 0.4762130677700043 |
| keywords[5].display_name | Machine learning |
| keywords[6].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[6].score | 0.46954450011253357 |
| keywords[6].display_name | Artificial intelligence |
| keywords[7].id | https://openalex.org/keywords/process |
| keywords[7].score | 0.4629422426223755 |
| keywords[7].display_name | Process (computing) |
| keywords[8].id | https://openalex.org/keywords/hyper-heuristic |
| keywords[8].score | 0.4287901818752289 |
| keywords[8].display_name | Hyper-heuristic |
| keywords[9].id | https://openalex.org/keywords/mathematical-optimization |
| keywords[9].score | 0.42153671383857727 |
| keywords[9].display_name | Mathematical optimization |
| keywords[10].id | https://openalex.org/keywords/mathematics |
| keywords[10].score | 0.17196449637413025 |
| keywords[10].display_name | Mathematics |
| language | en |
| locations[0].id | doi:10.1609/aaai.v32i1.12211 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4210191458 |
| locations[0].source.issn | 2159-5399, 2374-3468 |
| locations[0].source.type | conference |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2159-5399 |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | Proceedings of the AAAI Conference on Artificial Intelligence |
| locations[0].source.host_organization | https://openalex.org/P4310320058 |
| locations[0].source.host_organization_name | Association for the Advancement of Artificial Intelligence |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310320058 |
| locations[0].source.host_organization_lineage_names | Association for the Advancement of Artificial Intelligence |
| locations[0].license | |
| locations[0].pdf_url | https://ojs.aaai.org/index.php/AAAI/article/download/12211/12070 |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Proceedings of the AAAI Conference on Artificial Intelligence |
| locations[0].landing_page_url | https://doi.org/10.1609/aaai.v32i1.12211 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5008961324 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-1113-2899 |
| authorships[0].author.display_name | Wei Xia |
| authorships[0].countries | SG |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I165932596 |
| authorships[0].affiliations[0].raw_affiliation_string | National University of Singapore |
| authorships[0].institutions[0].id | https://openalex.org/I165932596 |
| authorships[0].institutions[0].ror | https://ror.org/01tgyzw49 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I165932596 |
| authorships[0].institutions[0].country_code | SG |
| authorships[0].institutions[0].display_name | National University of Singapore |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Wei Xia |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | National University of Singapore |
| authorships[1].author.id | https://openalex.org/A5028568420 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-1188-7474 |
| authorships[1].author.display_name | Roland H. C. Yap |
| authorships[1].countries | SG |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I165932596 |
| authorships[1].affiliations[0].raw_affiliation_string | National University of Singapore |
| authorships[1].institutions[0].id | https://openalex.org/I165932596 |
| authorships[1].institutions[0].ror | https://ror.org/01tgyzw49 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I165932596 |
| authorships[1].institutions[0].country_code | SG |
| authorships[1].institutions[0].display_name | National University of Singapore |
| authorships[1].author_position | last |
| authorships[1].raw_author_name | Roland Yap |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | National University of Singapore |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://ojs.aaai.org/index.php/AAAI/article/download/12211/12070 |
| open_access.oa_status | diamond |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Learning Robust Search Strategies Using a Bandit-Based Approach |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T12101 |
| primary_topic.field.id | https://openalex.org/fields/18 |
| primary_topic.field.display_name | Decision Sciences |
| primary_topic.score | 0.9973000288009644 |
| primary_topic.domain.id | https://openalex.org/domains/2 |
| primary_topic.domain.display_name | Social Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1803 |
| primary_topic.subfield.display_name | Management Science and Operations Research |
| primary_topic.display_name | Advanced Bandit Algorithms Research |
| related_works | https://openalex.org/W2165127677, https://openalex.org/W4286471047, https://openalex.org/W3165734945, https://openalex.org/W3049051839, https://openalex.org/W1991970232, https://openalex.org/W3190612470, https://openalex.org/W2140486203, https://openalex.org/W1068348394, https://openalex.org/W2734168857, https://openalex.org/W4200460889 |
| cited_by_count | 21 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 2 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 2 |
| counts_by_year[2].year | 2023 |
| counts_by_year[2].cited_by_count | 1 |
| counts_by_year[3].year | 2022 |
| counts_by_year[3].cited_by_count | 2 |
| counts_by_year[4].year | 2021 |
| counts_by_year[4].cited_by_count | 3 |
| counts_by_year[5].year | 2020 |
| counts_by_year[5].cited_by_count | 7 |
| counts_by_year[6].year | 2018 |
| counts_by_year[6].cited_by_count | 4 |
| locations_count | 1 |
| best_oa_location.id | doi:10.1609/aaai.v32i1.12211 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4210191458 |
| best_oa_location.source.issn | 2159-5399, 2374-3468 |
| best_oa_location.source.type | conference |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2159-5399 |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | Proceedings of the AAAI Conference on Artificial Intelligence |
| best_oa_location.source.host_organization | https://openalex.org/P4310320058 |
| best_oa_location.source.host_organization_name | Association for the Advancement of Artificial Intelligence |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310320058 |
| best_oa_location.source.host_organization_lineage_names | Association for the Advancement of Artificial Intelligence |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://ojs.aaai.org/index.php/AAAI/article/download/12211/12070 |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Proceedings of the AAAI Conference on Artificial Intelligence |
| best_oa_location.landing_page_url | https://doi.org/10.1609/aaai.v32i1.12211 |
| primary_location.id | doi:10.1609/aaai.v32i1.12211 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4210191458 |
| primary_location.source.issn | 2159-5399, 2374-3468 |
| primary_location.source.type | conference |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2159-5399 |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | Proceedings of the AAAI Conference on Artificial Intelligence |
| primary_location.source.host_organization | https://openalex.org/P4310320058 |
| primary_location.source.host_organization_name | Association for the Advancement of Artificial Intelligence |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310320058 |
| primary_location.source.host_organization_lineage_names | Association for the Advancement of Artificial Intelligence |
| primary_location.license | |
| primary_location.pdf_url | https://ojs.aaai.org/index.php/AAAI/article/download/12211/12070 |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Proceedings of the AAAI Conference on Artificial Intelligence |
| primary_location.landing_page_url | https://doi.org/10.1609/aaai.v32i1.12211 |
| publication_date | 2018-04-26 |
| publication_year | 2018 |
| referenced_works | https://openalex.org/W7075680496, https://openalex.org/W2244307845, https://openalex.org/W2257116377, https://openalex.org/W2227618531, https://openalex.org/W137179583, https://openalex.org/W6676077707, https://openalex.org/W6622345449, https://openalex.org/W157259654, https://openalex.org/W6724046077, https://openalex.org/W2144137480, https://openalex.org/W1584353551, https://openalex.org/W6629679810, https://openalex.org/W1704704531, https://openalex.org/W6705096242, https://openalex.org/W6713227295, https://openalex.org/W6759074759, https://openalex.org/W1499680727, https://openalex.org/W6633928019, https://openalex.org/W2039522160, https://openalex.org/W6750302219, https://openalex.org/W4234228486, https://openalex.org/W2913800047, https://openalex.org/W4254113915, https://openalex.org/W2317700292, https://openalex.org/W4285719527, https://openalex.org/W2108738385, https://openalex.org/W1568944559, https://openalex.org/W2403395836, https://openalex.org/W753461214, https://openalex.org/W2345096204, https://openalex.org/W2168405694, https://openalex.org/W1498636114, https://openalex.org/W2951854233, https://openalex.org/W2963368312 |
| referenced_works_count | 34 |
| abstract_inverted_index.a | 17, 26, 62 |
| abstract_inverted_index.In | 29 |
| abstract_inverted_index.It | 95 |
| abstract_inverted_index.is | 21, 24, 53, 70, 87 |
| abstract_inverted_index.of | 2, 42, 64 |
| abstract_inverted_index.or | 9, 15 |
| abstract_inverted_index.to | 46, 71 |
| abstract_inverted_index.we | 38 |
| abstract_inverted_index.Our | 51 |
| abstract_inverted_index.The | 68 |
| abstract_inverted_index.and | 23, 59 |
| abstract_inverted_index.can | 96 |
| abstract_inverted_index.our | 84 |
| abstract_inverted_index.set | 63 |
| abstract_inverted_index.the | 40, 56, 91, 99 |
| abstract_inverted_index.use | 41 |
| abstract_inverted_index.also | 97 |
| abstract_inverted_index.from | 61 |
| abstract_inverted_index.give | 77 |
| abstract_inverted_index.goal | 69 |
| abstract_inverted_index.good | 8, 18 |
| abstract_inverted_index.more | 88 |
| abstract_inverted_index.show | 82 |
| abstract_inverted_index.than | 33, 90 |
| abstract_inverted_index.that | 83 |
| abstract_inverted_index.this | 30 |
| abstract_inverted_index.often | 5, 25 |
| abstract_inverted_index.where | 55 |
| abstract_inverted_index.which | 76 |
| abstract_inverted_index.during | 66 |
| abstract_inverted_index.learns | 58 |
| abstract_inverted_index.manual | 27 |
| abstract_inverted_index.obtain | 72 |
| abstract_inverted_index.online | 54 |
| abstract_inverted_index.paper, | 31 |
| abstract_inverted_index.rather | 32 |
| abstract_inverted_index.robust | 78, 89 |
| abstract_inverted_index.search | 11, 19, 36, 49, 74, 93 |
| abstract_inverted_index.select | 48 |
| abstract_inverted_index.solver | 57 |
| abstract_inverted_index.propose | 39 |
| abstract_inverted_index.search. | 67 |
| abstract_inverted_index.selects | 60 |
| abstract_inverted_index.solving | 1 |
| abstract_inverted_index.However, | 13 |
| abstract_inverted_index.adaptive | 85 |
| abstract_inverted_index.approach | 52 |
| abstract_inverted_index.choosing | 7, 14 |
| abstract_inverted_index.learning | 44 |
| abstract_inverted_index.manually | 34 |
| abstract_inverted_index.original | 92, 100 |
| abstract_inverted_index.problems | 4 |
| abstract_inverted_index.process. | 28 |
| abstract_inverted_index.requires | 6 |
| abstract_inverted_index.specific | 10 |
| abstract_inverted_index.Effective | 0 |
| abstract_inverted_index.automatic | 73 |
| abstract_inverted_index.designing | 16 |
| abstract_inverted_index.heuristic | 20 |
| abstract_inverted_index.technique | 86 |
| abstract_inverted_index.constraint | 3 |
| abstract_inverted_index.heuristics | 65, 75 |
| abstract_inverted_index.outperform | 98 |
| abstract_inverted_index.techniques | 45 |
| abstract_inverted_index.Preliminary | 80 |
| abstract_inverted_index.experiments | 81 |
| abstract_inverted_index.heuristics, | 37 |
| abstract_inverted_index.heuristics. | 12, 50, 94, 101 |
| abstract_inverted_index.non-trivial | 22 |
| abstract_inverted_index.bandit-based | 43 |
| abstract_inverted_index.performance. | 79 |
| abstract_inverted_index.automatically | 47 |
| abstract_inverted_index.choosing/designing | 35 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| citation_normalized_percentile.value | 0.95775862 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |