Maswali ya AlphaGo na AlphaZero

Majibu na maelezo huonekana unapojibu maswali.

1. Kwa nini mchezo wa Go ulizingatiwa kuwa mgumu sana kwa kompyuta?
   • Ina idadi kubwa ya astronomia ya nafasi zinazowezekana
   • Ina hatua chache sana zinazowezekana
   • Inachezwa tu kwenye karatasi
   • Haina kanuni
2. Ni nani aliyeshinda AlphaGo maarufu 4-1 mnamo 2016?
   • Garry Kasparov
   • Lee Sedol
   • Magnus Carlsen
   • Amateur bila mpangilio
3. Which three games did AlphaZero’s paper evaluate?
   • Go, chess, and shogi
   • Poker, bridge, and backgammon
   • Atari, StarCraft, and Dota
   • Only Go and chess
4. AlphaZero inaoanisha njia gani ya utafutaji na mtandao wake wa neva?
   • Utafutaji wa binary wa kitabu cha simu
   • Urejeshaji wa mstari
   • Aina ya Bubble
   • Utafutaji wa Mti wa Monte Carlo
5. Ni mambo gani mawili ambayo mtandao wa neural wa AlphaZero unatabiri kuongoza utafutaji wake?
   • Sera (hatua nzuri) na thamani (nani anashinda)
   • Hali ya hewa na wakati
   • Jina na umri wa mpinzani
   • Rangi na sauti
6. What did MuZero add to the AlphaZero-style planning approach?
   • A requirement for human game records
   • A learned model of reward and environment dynamics used for planning without being given the rules
   • A replacement for all tree search
   • A fixed database of every possible board position
7. What information did AlphaZero need in its board-game experiments besides self-play?
   • A database of professional games
   • A complete endgame table for every position
   • The rules of the games
   • Human rankings for every possible move
8. How did the original AlphaGo system combine supervised and reinforcement learning?
   • It trained a policy from expert games and then improved through self-play
   • It used only random moves and never trained on human games
   • It learned the game rules from images without playing
   • It relied only on a fixed database of winning games