quiz bu lëkkale ak tegtal · Diggante Niveau
Xalaatal sa bopp ci quiz Agent Loops
Saytu ni xalaatu ndawu liggéey bi di jëfandikoo jaar-jaaru jëf, feedback bu bawoo ci biti, fàttaliku episodik ak ŋàññi ngir tegtal beneen jéem.
Laaj 1 de 8
Lan la xalaat sa bopp di yokk ci bouclage agent buñ miin?
Xoolaatal laaj bu nekk8 laaj
Sooy def quiz bi, tontu yi ak leeral yi dañuy feeñ.
- Lan la xalaat sa bopp di yokk ci bouclage agent buñ miin?
- Jéego buñ jël ci xel, fu model bi di ŋàññi liggéeyam balaa muy wéy
- Modèle bu gëna gaaw buy sànni woote jumtukaay
- Palanteer bu gëna mag ci saasi
- nit ku xoolaat jéego bu nekk
- Ci biir kaadar Reflexion, fan lañu denc ŋàññi boppam bu model bi?
- Ci diisaay yiñ defar bu baax ci model bi
- Ci biir benn tampon mémoire episodique buñuy jëfandikoo ci jéem yépp
- Ci base de done bu wuute, model bi mënul jàng
- Jéego bu nekk dañu leen di sànni
- Ban siñaal feedback ngir xalaat moo gëna wóor?
- Koolute boppam ci model bi kese
- Guddaayig tontu bu njëkk bi
- Siñaal yu bawoo ci biti yu melni njariñu test wala mesaasu njuumte ci jumtukaay
- Jamono jiñ jël ngir tontu
- Lan mooy anam wuñu xamee ci xalaat sa bopp bu baaxul?
- Dafay tax model bi gëna yeex nit ñi
- Dafay yàq ba fàww done yiñ tàggat
- Mën nañu ko jëfandikoo ludul ci liggéey nataal
- Royuwaay bi mën na wax ni tontu bu jaarul yoon moo jub
- naka la ko Self-Refine di defaree feedback?
- Jëfandikoo benn model ngir ŋàññi ba noppi binndaat limu génne
- Soo laajee API bu beneen liggéeyukaay
- Soo laajee jëfandikukat bi mu jox tolluwaayu jeton bu nekk
- Soo dindi bépp jëfandikoo jumtukaay
- Lan moo waral xalaat am solo lool ci liggéey yu bari jéego yu melni kodage wala navigation web?
- Ndax liggéey yooyu duñu musa jur njuumte
- Ndax jéem-jéem benn-pass dafay faral di lajj waaye ŋàññi-ak-jéemaat dafay am ndam
- Ndax xalaat dindi na soxla bépp jumtukaay
- Ndax dafay dindi soxla am mébet
- In a reflection loop, why is a failing unit test useful evidence for the next attempt?
- It proves the model’s self-critique is correct
- It updates model weights automatically
- It provides an external, concrete signal about which behavior did not meet the requirement
- It guarantees the entire program is wrong
- If an agent stores a critique in memory but does not fine-tune its model, how can that critique affect the next attempt?
- It changes the base model’s parameters permanently
- It changes the programming language
- It disables the external tool
- It can be retrieved and inserted into the next prompt as context