Qaababka Adduunka iyo Kediska Simulators ee la Bartay

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

1. Waa maxay shaqada asaasiga ah ee moodeelka aduunka?
   • Si loo saadaaliyo sida deegaanku isu beddelo marka la eego dawlad iyo waxqabad
   • Si loo calaamadiyo sawirada qaybaha
   • Si aad qoraalka ugu dhejiso dhejisyada
   • Si loo maro xirmooyinka shabakada
2. In the 2018 World Models DoomTakeCover experiment, where was the controller trained?
   • Kaliya on hardware dhabta ah
   • Gudaha moodeelka 'riyada' deegaanka ee la bartay
   • Oo saaran koox daruuro dadweyne oo robots ah
   • Isticmaalka xogta luqadda kaliya
3. Waa maxay waxqabadka caanka ah ee DeepMind's DreamerV3 ku guuleystey?
   • Qorista sheeko sheeko
   • Turjumaada 100 luqadood
   • Collecting diamonds in Minecraft using policy learning from imagined trajectories
   • Dejinta microchip
4. Muxuu sameeyaa Google's Genie?
   • Ku cadaadiya fiidyaha si loo daawado
   • Kala soocida natiijooyinka raadinta
   • Wuxuu tababaraa macallimiinta luqadda
   • Wuxuu abuuraa la kontrooli karo, la ciyaari karo adduunyo 2D ah oo ka soo jeeda muuqaallo iyo muuqaal aan sumad lahayn
5. Sidee bay moodooyin badan oo adduunku u ilaalinayaan dhibka saadaasha ee la heli karo agabka cabbirka sare leh sida sawirrada?
   • Waxay u xejiyaan indha-indhaynta xaalad qarsoon oo kooban waxayna ku saadaaliyaan meesha bannaan
   • Waxay iska indhatiraan sawirada gabi ahaanba
   • Waxay isticmaalaan maqal kaliya
   • Waxay kaydiyaan jir kasta oo ceeriin weligood
6. What is a potential motivation for using a world model in robotics?
   • Guarantee every simulated action is safe to deploy
   • Explore candidate actions in learned dynamics with fewer real-world interactions, while validating model accuracy
   • Avoid testing the model against any real observations
   • Prove a visually realistic frame is physically accurate
7. What techniques did DreamerV3 report for improving learning stability across diverse domains?
   • A fixed image resize and no reward modeling
   • A hand-written controller for every game
   • Normalization, balancing, and transformations
   • Removing all state observations from training
8. Why does visually plausible output from a learned simulator not by itself prove accurate dynamics?
   • Visual models cannot process actions
   • Every rendered image is a ground-truth sensor measurement
   • Plausibility guarantees accurate forces and collisions
   • A realistic-looking frame may still depict incorrect physical state changes