Concept
AlphaGo
Related concepts (14)
Reinforcement learning
Reinforcement learning (RL) is an area of machine learning concerned with how intelligent agents ought to take actions in an environment in order to maximize the notion of cumulative reward. Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning and unsupervised learning. Reinforcement learning differs from supervised learning in not needing labelled input/output pairs to be presented, and in not needing sub-optimal actions to be explicitly corrected.
Shogi
, also known as Japanese chess, is a strategy board game for two players. It is one of the most popular board games in Japan and is in the same family of games as Western chess, chaturanga, xiangqi, Indian chess, and janggi. Shōgi means general's (shō 将) board game (gi 棋). Shogi was the earliest historical chess-related game to allow captured pieces to be returned to the board by the capturing player. This drop rule is speculated to have been invented in the 15th century and possibly connected to the practice of 15th-century mercenaries switching loyalties when captured instead of being killed.
Deep learning
Deep learning is part of a broader family of machine learning methods, which is based on artificial neural networks with representation learning. The adjective "deep" in deep learning refers to the use of multiple layers in the network. Methods used can be either supervised, semi-supervised or unsupervised.
Artificial intelligence
Artificial intelligence (AI) is the intelligence of machines or software, as opposed to the intelligence of human beings or animals. AI applications include advanced web search engines (e.g., Google Search), recommendation systems (used by YouTube, Amazon, and Netflix), understanding human speech (such as Siri and Alexa), self-driving cars (e.g., Waymo), generative or creative tools (ChatGPT and AI art), and competing at the highest level in strategic games (such as chess and Go).