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General game playing (GGP) is the design of artificial intelligence programs to be able to play more than one game successfully. [ 1 ] [ 2 ] [ 3 ] For many games like chess, computers are programmed to play these games using a specially designed algorithm, which cannot be transferred to another context.
It was designed to play human opponents in games of noughts and crosses (tic-tac-toe) by returning a move for any given state of play and to refine its strategy through reinforcement learning. This was one of the first types of artificial intelligence.
Multi-agent reinforcement learning (MARL) is a sub-field of reinforcement learning. It focuses on studying the behavior of multiple learning agents that coexist in a shared environment. [ 1 ] Each agent is motivated by its own rewards, and does actions to advance its own interests; in some environments these interests are opposed to the ...
For example, the outcome of a game (i.e., whether one player won or lost) can be easily measured without providing labeled examples of desired strategies. Neuroevolution is commonly used as part of the reinforcement learning paradigm, and it can be contrasted with conventional deep learning techniques that use backpropagation ( gradient descent ...
Reinforcement learning is a behavioral learning model where the algorithm provides data analysis feedback, directing the user to the best result. It enables an agent to learn through the ...
Reinforcement learning (RL) is an interdisciplinary area of machine learning and optimal control concerned with how an intelligent agent should take actions in a dynamic environment in order to maximize a reward signal. Reinforcement learning is one of the three basic machine learning paradigms, alongside supervised learning and unsupervised ...
With zero knowledge built in, the network learned to play the game at an intermediate level by self-play and TD(). Seminal textbooks by Sutton and Barto on reinforcement learning, [6] Bertsekas and Tsitiklis on neuro-dynamic programming, [7] and others [8] advanced knowledge and interest in the field.
The game state is the assembly program generated up to a given point. The game move is an extra instruction appended to the current assembly program. The game's reward is a function of the assembly program's correctness and latency. To reduce cost, AlphaDev only computes actual measured latency on less than 0.002% of generated programs, as it ...