MCQ IN COMPUTER SCIENCE & ENGINEERING

Detailed explanation-1: -Reinforcement learning applications Learning to play board games such as Go, shogi, and chess is not the only area where reinforcement learning has been applied. Two other areas are playing video games and teaching robots to perform tasks independently.

Detailed explanation-2: -Reinforcement Learning Chess is a series of notebooks where I implement Reinforcement Learning algorithms to develop a chess AI. I start of with simpler versions (environments) that can be tackled with simple methods and gradually expand on those concepts untill I have a full-flegded chess AI.

Detailed explanation-3: -Reinforcement Learning in gaming Let’s look at an application in the gaming frontier, specifically AlphaGo Zero. Using reinforcement learning, AlphaGo Zero was able to learn the game of Go from scratch. It learned by playing against itself.

Detailed explanation-4: -Our chess engine proved that reinforcement learning in combina-tion with the classification of board state leads to a notable improvement, when compared with other engines that only use reinforcement learning, such as KnightCap.