[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"branding":3,"analytics":7,"article-delphos-uses-reinforcement-learning-to-speed-choice-modeling":10,"sections":41},{"siteName":4,"siteTagline":5,"publisherName":4,"contactEmail":6},"The Revision","Tech news, decoded.","editor@therevision.news",{"gaMeasurementId":8,"adsenseClientId":9},"G-ZW2MV82GYR","ca-pub-8533917693782264",{"article":11},{"id":12,"slug":13,"title":14,"dek":15,"body_md":16,"tags_json":17,"published_at":18,"created_at":19,"updated_at":20,"status":21,"review_note":22,"review_notes":23,"image_url":22,"persona_id":22,"persona_name":22,"section":30,"tags":31,"sources":36,"feedback":40,"feedback_at":22,"cost_usd":40,"total_tokens":40},6620,"delphos-uses-reinforcement-learning-to-speed-choice-modeling","Delphos Uses Reinforcement Learning to Speed Choice Modeling","A new reinforcement learning system called Delphos learns to specify transport choice models across datasets, cutting trial and error for researchers.","A new AI system called Delphos can specify and test transport choice models nearly as well as expert modellers, according to a paper posted this week.\n\nResearchers built Delphos as a multitask reinforcement learning framework that treats model specification as a sequence of decisions, applying modelling actions and getting feedback from an estimation environment. It represents utility specifications as sets of modelling terms using a DeepSet-Q architecture, letting a single policy transfer what it learns across datasets that have different variables. The team trained Delphos on nine transport choice datasets, where it consistently outperformed single-task agents trained from scratch on one dataset at a time. Tested without further training on two datasets it had never seen, Swissmetro and Decisions, the same agent produced competitive specifications in under 20 minutes on a standard CPU, beating a VNS metaheuristic on Swissmetro and matching a published expert-built specification on Decisions.\n\nChoice model specification is a time-consuming task, since modellers have to juggle goodness-of-fit, parsimony, and behavioural plausibility across multiple candidate models. A tool that reuses experience across datasets and narrows the search space could cut a lot of that manual trial-and-error, all without taking the modeller out of the loop for diagnosis and final selection.\n\nMatching a human-built specification and beating a classic metaheuristic on two unseen datasets is a genuinely useful result. But \"competitive with experts\" is not the same as \"better than experts\": for now, Delphos looks like a fast first draft, not a replacement modeller.","[\"reinforcement-learning\",\"transportation-modeling\",\"ai-research\",\"choice-modeling\"]","2026-09-17T04:00:00.000Z","2026-09-18T02:58:38.851Z","2026-09-18T02:58:50.771Z","published",null,[24],{"id":25,"reviewer":26,"round":27,"reason":28,"status":29},"editor-r1","editor",1,"Remove or attribute the invented claim that manual specification 'used to take modellers days' — the source only calls it 'time-consuming' and never states a duration, so the 20-minutes-vs-days comparison is an unsupported fabricated statistic.","resolved","ai",[32,33,34,35],"reinforcement-learning","transportation-modeling","ai-research","choice-modeling",[37],{"name":38,"url":39},"arXiv cs.AI","https:\u002F\u002Farxiv.org\u002Fabs\u002F2609.18441",0,{"sections":42},[43,47,51,56,61,65,69,74,79,83,88,93,98,103],{"name":44,"slug":30,"count":45,"latest_published_at":46},"AI",3852,"2026-09-17T08:27:09.000Z",{"name":48,"slug":49,"count":50,"latest_published_at":18},"Security","security",648,{"name":52,"slug":53,"count":54,"latest_published_at":55},"Policy","policy",338,"2026-09-11T04:00:00.000Z",{"name":57,"slug":58,"count":59,"latest_published_at":60},"Deals","deals",179,"2026-06-29T20:02:07.000Z",{"name":62,"slug":63,"count":64,"latest_published_at":18},"Hardware","hardware",154,{"name":66,"slug":67,"count":68,"latest_published_at":18},"Science","science",114,{"name":70,"slug":71,"count":72,"latest_published_at":73},"Consumer Tech","consumer-tech",99,"2026-09-09T17:27:33.000Z",{"name":75,"slug":76,"count":77,"latest_published_at":78},"Software","software",75,"2026-09-10T20:41:21.000Z",{"name":80,"slug":81,"count":82,"latest_published_at":18},"Dev Tools","dev-tools",73,{"name":84,"slug":85,"count":86,"latest_published_at":87},"Startups","startups",55,"2026-09-09T23:14:29.000Z",{"name":89,"slug":90,"count":91,"latest_published_at":92},"Gaming","gaming",43,"2026-09-10T12:18:06.000Z",{"name":94,"slug":95,"count":96,"latest_published_at":97},"General","general",41,"2026-09-08T01:57:23.000Z",{"name":99,"slug":100,"count":101,"latest_published_at":102},"Reviews","reviews",20,"2026-06-24T12:00:01.000Z",{"name":104,"slug":105,"count":106,"latest_published_at":107},"How-To","how-to",6,"2026-06-16T09:00:00.000Z"]