Seetug garabu Monte Carlo

Sooy def quiz bi, tontu yi ak leeral yi dañuy feeñ.

1. Lan mooy ñeenti jéego yu mag yi ci seetlu garabu Monte Carlo?
   • Tanneef, yaatal, simulation, tasaare ci ginaaw
   • Tànn, segg, boole, genne
   • Kode, dekode, jaar, wax luy waaja am
   • Taggat, saytu, natt, dugal
2. Lan mooy balance formula tànneef UCT?
   • Gaawaay ak mémoire
   • Jëfandikoo toxu yu am solo ak banneexu yi ñu gëna néew seeti
   • Taggat ak jël doggal
   • Yaatu ak xóotaayu reso bi
3. Ci MCTS bu yàgg bi, lan mooy xew ci jéego 'simulation' (defar)?
   • Garab gi dafa efaase
   • Reseau neuronal bi deñuko taggaat
   • Po mu ngi jouer ci ab résultat bu bawoo ci node bu bees bi
   • Xale yépp dañu leen yaatal benn yoon
4. What roles did AlphaGo’s policy and value networks play in its MCTS search?
   • The policy network computed transitions and the value network chose the root child
   • Both networks performed random rollouts without evaluating positions
   • The value network proposed legal moves while the policy network estimated terminal rewards
   • The policy network guided move selection and the value network estimated position strength; AlphaGo also used a rollout policy
5. Ginaaw ñu baamtu ko lu bari, naka la MCTS di faral di tànnee jéego bu mujj bi ñuy jouer?
   • Xale root bi gëna bari vizite
   • Demaat bi gëna am mbégte ci saasi
   • Xale bu bari
   • Node bi gëna xóot ci garab gi
6. Lan moo tax MuZero gëna fës buñu ko méngale ak AlphaZero?
   • Jëfandikuwul benn reso neuronal
   • Dafay jàng modelu boppam ci environmaa bi, suko defee mu mëna waajal te kenn duko jox ay sàrt
   • Go rek lay jouer
   • Dafa bàyyi seetlu garab
7. In the UCT selection score, what does the exploration term reward?
   • Only the child with the highest raw reward
   • Moves that have already been selected most often, regardless of value
   • Children with fewer visits relative to their parent, encouraging further sampling
   • A random rollout’s final board size
8. Which MCTS iteration step adds a new child to the existing tree?
   • Selection
   • Simulation
   • Tasaaro ci ginaaw
   • Expansion