Jàngale buy dooleel ci net bi
Njàngalem dooleel bi nekk ci biti dafay tàggat ndawu liggéey yi ci ay done yuñ dajale bu njëkk, te amul benn jaxasoo ci environmaa bi.
Résumé
It matters because in healthcare, robotics, and recommendation, exploring by trial and error is too costly, slow, or dangerous.
Plongeur bu xóot
Offline RL (ñu koy woowe itam batch RL) dafay jàng benn politik ci benn log static ci jaar-jaar yu njëkk - réew, jëf, neexal, ak réew yi ci topp - te musul jël jëf yu bees ci environmaa bi dëgg ci diiru tàggat. Loolu dafay ubbi RL ci jekkal yi nga xamni seetlu ci net bi wóorul wala seer, lu melni jàng sàrti pajum ci dokimaa malaad yu yàgg yi wala xam-xam robot ci done yiñ dugal. Jafe-jafe bi gëna fësal mooy coppite ci séddale bi boole ci njuumte ci extrapolation: pexe yu sukkandiko ci valeur standard dañuy ëpp valeur jëf yu génn ci séddale yi dataset bi musul jéem, te amul benn environmaa buy saafara njuumte yooyu, politik bi dafay topp neexal yu baaxul. Algorithm yu bees yi dañuy xeex loolu ci jege done yi, jëfandikoo xayma valeur conservative (CQL), tënk politik (BCQ, BEAR), wala pondération implicite (IQL).
Gis-gis xarala
Modu njuumte bu mag bi mooy gëna xayma jëf yi nekk ci bitti séddale bi: fonction Q bi ñu jàng dafay jox valeur yu bari tànneefi jëf yi nekkul ci dataset bi, ba noppi bootstrapping dafay tasaare njuumte yooyu te amul benn feedback bu dëggu ngir saafara leen. Conservative Q-Learning (CQL) dafay saafara jafe-jafe yii ci yokk benn regularizer buy wàññi Q-valeur yi ngir jëf yuñu gisul, fekk jëf yi ci done yi dañu yéeg, ba noppi génne ay yamaleg valeur dëgg ak politik buy moytu tànneef yu amul ndimmbal, yu ëpp yaakaar.
njeextalu pexe
Njëgg ak budget
Dogal yi architecture di jël dañuy indi njariñ ak njëgu liggéey bi ay at ci ginaaw.
dogal yu gëna leer
Njàngalem xarala yi dafay jàppale ekip yi ñu tànn li gën, te baña yam ci li gëna bees daal.
Xool kalite
Tanneef yu gëna baax ci wàllu ingeñër dina wàññi jafe-jafe yi ci wàllu wóor ci liggéey bi.
Ëlëgu jàng buy dooleel ci net bi
Offline RL dafay jaxasoo ak modeling yu toppalante - jegewaale yu melni Decision Transformer recast ko muy wax luy waaja am ci jëf yi ñu bëgg - ak ak tàggat bu yaatu, may agent yi ñu tàggat ci done yu bari yuñ dugal ci net bi. Xaarandil màgg ci wàllu faju, dawal boppam, ak xalaat fu jàng bu wóor ci done yi fi nekk nekk lu am solo, ci wetu jumtukaay yu gëna baax ngir jàngat politik yi nekk ci biti, suko defee ñu mëna wóolu politik yiñ dugal laataa ñuy jëfandikoo ci àdduna dëgg.
Doxal ci àdduna dëgg
Jàng sàrti pajum klinik ci done elektronik yu yàgg
Taggat robot yu bawoo ci ay done yu bari te du am benn wërsëg bu am risk
Optimiser sistemu recommande ak publicité ci journal interaction yu njëkk ya
Yokkatal politiku dogal ci dawal boppam ci done yuñ dajale
Risk yi ak balustrade yi
Optimize benn benchmark mën na nëbb ñakk kattan yu gëna yaatu ci sistem bi.
Njëg li ñuy fay ci infrastructure yi ak ci toppatoo dañuy faral di suufeel.
Bu sistem yi di gëna xawa jafee xam, jafe-jafe yi am ci wàllu kaaraange ak seetlu mën nañu gëna bari.
Roadmap ngir samp gi
Mandargal latency, kalite, ak njëg yi laata ngay jëfandikoo.
Benchmark ci biir sargal ak done yu dëggu.
Jumtukaay bi di saytu njuumte yi, derive bi ak njeextalu jëfandikukat bi.
Waajal rollback ak yooni tontu ci jafe-jafe yi laata ngay eskale.
Weyal di banneexu
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Gis bi ci topp
Jàngat bu am doole ci feedback nit
Laaj yi ñuy faral di laaj
What is Offline Reinforcement Learning?
Njàngalem dooleel bi nekk ci biti dafay tàggat ndawu liggéey yi ci ay done yuñ dajale bu njëkk, te amul benn jaxasoo ci environmaa bi. Dafa am solo ndax ci wàllu faju, robotik, ak tegtal, jàngat ak njuumte lu seer la, yeex, wala lu jafee gis.
Lan mooy jàngale dooleel ci net bi (batch)?
Offline RL dafay jàng benn politik ci done yiñ njëkka dajale te du musa jaxasoo ak environmaa bi ci diiru tàggat yaram.
Lan mooy jafe-jafe teknik bi gëna mag ci RL offline?
Pexem valeur yi dañuy gëna fonk jëf yi amul ci dataset bi, te amul environmaa bu ñuy saafara njuumte yooyu, politik bi dafay topp ay neexal yu baaxul.
Lan moo waral RL offline neex ci aplikaasioŋu xeet jàngoro?
Jàngat ak njuumte ci malaad yi lu jafee xam la, kon jàng xeeti paj yi ci dokimaa yu yàgg yi dina moytu teg nit ñi ci jafe-jafe.
naka lay def ba Q-Learning (CQL) di xeex lu ëpp luñuy xool?
CQL dafay yokk benn penalite buy wàññi Q-valeur yi ngir jëf yi nekkul ci done yi, fekk jëf yi ci biir done yi dañu yéeg, loolu mooy joxe benn limite bu gëna suufe ci valeur bi.
naka lay def ba soppi dogal ci RL bi nekk ci biti?
Decision Transformer dafay jàppee trajectoire yi ni ay toppu-topp ba noppi defar ay jëf yu lalu ci dellu-ci-dellu biñ bëgga, sànni doxalal ni otoregressive toppu-topp.