Abstract
We study the predict+optimise problem, where machine learning and combinatorial optimisation must interact to achieve a common goal. These problems are important when optimisation needs to be performed on input parameters that are not fully observed but must instead be estimated using machine learning. We provide a novel learning technique for predict+optimise to directly reason about the underlying combinatorial optimisation problem, offering a meaningful integration of machine learning and optimisation. This is done by representing the combinatorial problem as a piecewise linear function parameterised by the coefficients of the learning model and then iteratively performing coordinate descent on the learning coefficients. Our approach is applicable to linear learning functions and any optimisation problem solvable by dynamic programming. We illustrate the effectiveness of our approach on benchmarks from the literature.
| Original language | English |
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| Title of host publication | Proceedings of The Thirty-Fourth AAAI Conference on Artificial Intelligence |
| Editors | Vincent Conitzer, Fei Sha |
| Place of Publication | Palo Alto CA USA |
| Publisher | Association for the Advancement of Artificial Intelligence (AAAI) |
| Pages | 1444-1451 |
| Number of pages | 8 |
| ISBN (Electronic) | 9781577358350 |
| DOIs | |
| Publication status | Published - 2020 |
| Event | AAAI Conference on Artificial Intelligence 2020 - New York, United States of America Duration: 7 Feb 2020 → 12 Feb 2020 Conference number: 34th https://aaai.org/Conferences/AAAI-20/ (Website) |
Publication series
| Name | AAAI 2020 - 34th AAAI Conference on Artificial Intelligence |
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| Publisher | Association for the Advancement of Artificial Intelligence |
| Number | 2 |
| Volume | 34 |
| ISSN (Print) | 2159-5399 |
| ISSN (Electronic) | 2374-3468 |
Conference
| Conference | AAAI Conference on Artificial Intelligence 2020 |
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| Abbreviated title | AAAI 2020 |
| Country/Territory | United States of America |
| City | New York |
| Period | 7/02/20 → 12/02/20 |
| Other | The Thirty-Fourth AAAI Conference on Artificial Intelligence was held on February 7–12, 2020 in New York, New York, USA. The surge in public interest in AI technologies, which we have witnessed over the past few years, continued to accelerate in 2019–2020, with the societal and economic impact of AI becoming a central point of public and government discussion worldwide. AAAI-20 saw submissions and attendance numbers that were records in the history of the AAAI series of conferences and continued its tradition of attracting top-quality papers from all areas of AI. We were excited to see increases in submissions across almost all areas. The AAAI-20 program consisted of a core technical program of original research presentations, including a special track on AI for social impact and a sister conference track. It additionally featured a broad range of tutorials, workshops, invited talks, panels, student abstracts, a debate, and presentations by senior members. The program was rounded out by technical demonstrations, exhibits, an AI job fair, the AI in Practice program, a student outreach program, and a game night. The conference also continued its tradition of colocating with the long-running IAAI conference and the EAAI symposium, as well as the newer conference on AI, Ethics, and Society. |
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