{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T07:40:38Z","timestamp":1723016438177},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,8]]},"abstract":"<jats:p>We present a multi-agent learning algorithm, ALMA-Learning, for efficient and fair allocations in large-scale systems. We circumvent the traditional pitfalls of multi-agent learning (e.g., the moving target problem, the curse of dimensionality, or the need for mutually consistent actions) by relying on the ALMA heuristic as a coordination mechanism for each stage game. ALMA-Learning is decentralized, observes only own action\/reward pairs, requires no inter-agent communication, and achieves near-optimal (&lt;5% loss) and fair coordination in a variety of synthetic scenarios and a real-world meeting scheduling problem. The lightweight nature and fast learning constitute ALMA-Learning ideal for on-device deployment.<\/jats:p>","DOI":"10.24963\/ijcai.2021\/18","type":"proceedings-article","created":{"date-parts":[[2021,8,11]],"date-time":"2021-08-11T11:00:49Z","timestamp":1628679649000},"page":"125-131","source":"Crossref","is-referenced-by-count":2,"title":["Improving Multi-agent Coordination by Learning to Estimate Contention"],"prefix":"10.24963","author":[{"given":"Panayiotis","family":"Danassis","sequence":"first","affiliation":[{"name":"Artificial Intelligence Laboratory, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Florian","family":"Wiedemair","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Laboratory, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Boi","family":"Faltings","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Laboratory, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"number":"30","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2021","name":"Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}","start":{"date-parts":[[2021,8,19]]},"theme":"Artificial Intelligence","location":"Montreal, Canada","end":{"date-parts":[[2021,8,27]]}},"container-title":["Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2021,8,11]],"date-time":"2021-08-11T11:00:55Z","timestamp":1628679655000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2021\/18"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2021,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2021\/18","relation":{},"subject":[],"published":{"date-parts":[[2021,8]]}}}